The No-Code
Automation
Playbook
CONTENTS
04
INTRODUCTION
Thilo Huellmann, Co-Founder & CTO, Levity AI
05
MAPPING THE NO-CODE AI LANDSCAPE
Gero Keil, Co-Founder & CEO, Levity AI
14
HOW TO TRANSFORM YOUR COMPANY’S CHALLENGES INTO YOUR NEXT
PROMOTION WITH NO-CODE TOOLS
Philip Lakin, Co-Founder & CEO, Nocodeops
18
THE CENTRAL ROLE ZAPIER PLAYS IN THE NO-CODE SPACE
Andy Wingrave, Chief Automator, andywingrave.com
21
HOW TO LEVERAGE NO-CODE IN YOUR BUSINESS WITHOUT CODING
KNOWLEDGE
Hanna Kleinings, Customer Operations Manager, Levity AI
CONTENTS (CONT'D)
25
INTEGRATING NO-CODE AUTOMATION INTO SMES
Iulian Lupescu, Procesio
30
WHY EVERY BUSINESS CAN BENEFIT FROM AUTOMATION
Arne Wolfewicz, Growth, Levity AI
33
THE FUTURE OF NO-CODE APPLICATIONS WITH SOFTR’S COFOUNDER
Mariam Hakobyan, Co-Founder & CEO, Softr
INTRODUCTION
Thilo Huellmann
Co-Founder & CTO, Levity AI
When we started Levity we were in the same
position as our users. We wanted to process
large amounts of unstructured data (news
articles) and figured out that machine learning
was the only technique to do it in a scalable
way. We imagined a symbiotic system of
human and machine intelligence that allows us
to dump data every day into one place, the
machine would automatically process most of
the data and forward edge cases to humans in
a seamless interface. Over time the machine
would learn from human feedback and
improve.
Unfortunately, nothing catered to non-technical
people by orchestrating the business process
end-to-end while providing a simple UX and UI
and building the highest possible abstraction
layer on top of ML. So we started to build our
own (internal) tools.
We quickly realized that we're not the only ones
with this problem and decided to put out
internal tools in front of other people. Our goal
is to democratize AI-powered automation for
non-technical users to create a world without
mindless, repetitive work, making AI accessible
to non-tech users through self-explanatory UI.
No-code stands for a family of tools that allows
people to build web applications and systems
without having to program them.
This is possible because of the many direct and
indirect integrations between different tools, as
well as open interfaces (APIs), that allow data
to be exchanged more or less seamlessly. In
pre-cloud times, this used to be much harder to
set up and could generally only be achieved
through programming.
The no-code space is relatively new and
unknown to many. Despite its limitless potential,
the possibilities that no-code tools offer are still
perceived as unattainable by many. Our hope
is that this e-book serves as a guide for all
technical and non-technical people interested
in optimizing their business processes through
the effective use of no-code AI.
Hopefully, by the end you will be able to fully
comprehend, and even explain to someone
else, how to successfully optimize your
processes through the use of no-code AI. The
no-code space has a wide scope of
applications, but here we will intentionally
focus on business applications.
We hope you find this e-book as helpful as we
intended it to be when putting it together, and
we welcome any feedback you may have
regarding its contents.
MAPPING THE NOCODE AI LANDSCAPE
Gero Keil
Co-Founder & CEO, Levity AI
Introduction
No-code in a nutshell
While building our own platform, we have been
keeping a close eye on the no-code AI space.
We realized how difficult it was for nontechnical people to build custom AI solutions
and AI-powered process automation. That is
why we wanted to share this knowledge with
you.
For as long as there have been computers to
program, there have been attempts to make
programming easier, faster, less technical, and
available to a much broader audience.
While the no-code market is maturing as a
whole (Dreamweaver and MS Frontpage, the
first WYSIWYG (what you see is what you get)
solutions, both launched in 1997), certain subsegments are just emerging, making this space
more powerful. No-code AI is one of them. As
we are constantly observing the field, we
thought that sharing these insights would be
useful for you as well.
We are mapping out the intersection of nocode, SaaS, and AI: AI tools that don't require
any coding or infrastructure to be set up for
building powerful applications that can make
decisions that previously required human
judgment.
Essentially, any end-user programming signals
that even though most computer users lack
coding skills, they would welcome the
application potential of various tools – as long
as the effort to obtain these skills is low.
No-code stands for a family of tools that allow
people to build applications and systems
without having to program them in a
conventional way.
Instead, the core functionality is accessible
through visual interfaces and guided user
actions, as well as pre-built integrations with
other tools to exchange information as needed.
The No-Code Automation Playbook | page 5
While these self-imposed restrictions can lead
to issues for very large or complex applications,
the whole family of no-code tools is handing a
big chunk of power to their users. As Alex
Nichols from Alphabet's growth fund CapitalG
said:
"No-code is empowering business users
to take over functionality previously
owned by technical users by abstracting
complexity and centering around a
visual
workflow.
This
profound
generational shift has the power to
touch every software market and every
user across the enterprise."
To give you a few examples, here are some
common things that can be built entirely with
said no-code tools (check out Nocodelist for
more examples):
Websites and landing pages with Webflow
(ours is built with it!)
Web or mobile applications with Bubble,
Adalo, Mendix or Thunkable
Chatbots or virtual assistants through
Octane AI, Kore.ai, Landbot or mindsay
Databases through Airtable
Connecting your tool stack with Zapier,
tray.io, Integromat, Parabola or Paragon
E-commerce through Shopify or Weebly
Manage memberships with Memberstack
It is fair to believe that the no-code space is
here to stay. AI tools built on these principles
are showing that the field not only grows in
width but also depth when it comes to the job
to be done and technology in place.
Before we move to no-code AI, we will quickly
touch on one fundamental question first: When
does it even make sense to use AI?
When to use artificial
intelligence
Note that AI can be used for a variety of applications
but we intentionally limit our discussion to business
applications.
Broadly speaking, AI is particularly helpful
when there is some sort of intelligent
judgement to be made by humans and when
there are many of these on an ongoing basis.
We often use the phrase "AI starts where rulebased automation ends" – which makes sense
from our viewpoint but should not be
generalized (there are tools that go beyond
pure automation, e.g. Obviously AI for
analyzing tabular data at scale).
More practically, whether AI should be used or
not is a question of whether there are other
solutions that can do the job at the same (or
higher) level of quality, cost, or speed.
If so, they are generally better suited to do the
job. AI is (still) inherently fuzzy due to not being
explicitly programmed to do x.
The No-Code Automation Playbook | page 6
At the same time, explicit programming often
leads to problems when there are simply too
many rules or exceptions to be considered. In
that case, AI often works better. For example, it
is certainly possible to set up rule-based
automation for processing text by using a long
chain of words and phrases but in many
situations, this wouldn't be efficient due to high
costs or poor performance.
The promise of no-code AI
A vast amount of AI and Machine Learning
companies claim that they democratize AI and
this is probably true for their respective target
users, which oftentimes are still regular
engineers. Out of all these companies, those
that are building no-code tools get the closest
to the ideal of "any person without prior
training".
This increased level of democratization seems
overdue: It has been proven time and time
again, the majority of businesses struggle to
implement AI is its full potential and scale,
making the ease of this trade-off even more
crucial.
Easy-to-use ML platforms leverage the
time/value/knowledge
trade-off
in
a
genuinely attractive way and allow users with
no AI coding skills to optimize day-to-day
operations and to solve business issues.
Visual, often drag-and-drop, no-code AI tools
make AI less intimidating and more
comprehensible to non-technical people or
those who lack the time or resources to build
such systems from the ground up.
Besides this, there are some additional
advantages to no-code AI:
1. Accessibility
No-code AI enables organizations to make use
of AI in the first place and can act as the
stepping-stone towards intensified use of data
science or AI in the future. The comparably
low investment paired with people building up
hands-on knowledge of AI tools mitigate the
biggest obstacles to AI adoption at small and
mid-sized companies.
The No-Code Automation Playbook | page 7
No-code AI is still a rather growing market –
and most companies who operate in this space
tend to have positioned themselves in
technologies (NLP, Voice Recognition, Computer
Vision) vs specific use case management
(classification problems, CRM, web-builders,
business apps). It is often hard to draw the line
where one application ends and the other
starts – especially when we look at AI
applications.
To get a clearer picture, we decided to take a
deeper look into no-code AI players, and what
they offer. The list below is in no way
exhaustive, nor in any particular order (well...
alphabetical), and we will keep on adding new
players as they come – but bringing some
structure into the landscape was a necessity.
What made the most sense to us was grouping
based on core value proposition – we know
that many of these companies are active in
more than one scene. Leveraging the no-code
movement to become a maker is fantastic – but
we need to know what we want to create in the
first place.
In a nutshell, we took the following criteria to
qualify as no-code AI into account:
Tools that enable users to build solutions from
scratch, which would have previously required
one or more (ML) engineers to build.
Creates value on its own for users and
companies of all sizes – and is not just an
enterprise-level developer tool (think Uber's
Ludwig).
Usable by non-technical people – this is
essentially the core of the no-code movement.
More importantly, this is one of the criteria we
had the longest debate on. The level of
knowledge plays a key role - and while there
are tools like MS Azure, or C3 AI Suite, or even
deepCognition - they are not built for the
average knowledge worker, but for people
who already know what they are doing in the
developer stage.
We'll take a brief look into a selection of these
tools:
2. Usability
Plug-and-play allows for anyone in the
organization to find an AI solution to a
problem, and more often than not, in a budgetfriendly way. These tools are built with nontechnical users and non-developers in mind.
3. Speed
Mapping the no-code AI
landscape
There are some great tools already out there
(and plenty of resources – check out
MakerPad, Zeroqode, and NoCode – and we
thought that it would be a good idea to map
them out.
The best no-code AI platforms allow users to
iterate through the whole value chain of
machine learning quickly. This allows for more
rapid experimentation to see what can be done
using one's own data – and getting back to
business right afterwards. There is no better
way to convince someone than to show them
the process in a simple, intuitive way.
Besides providing a current snapshot of the
industry, it might also help better understand
subtle differences between seemingly similar
tools. For seasoned ML practitioners, this may
be obvious but no-code tools are addressing a
less technical audience by definition, so there's
that.
4. Quality
While observing the field, we noticed that two
dimensions stood out:
No-code tools are built for people who may not
possess a technical degree or even deep
expertise in the subject to begin with. This
requires extensive work going into the product
as sane defaults and safety measures need to
be carefully chosen on behalf of the user. To
further mitigate such risks, some AI platforms
have human review built-in and ask for input
when needed. This combination reduces the
human error when setting up such systems in
the first place and allows direct interaction with
the platform during daily operations.
5. Scalability
AI itself doesn't care whether it performs a task
for a single or a hundred users and neither do
servers that are automatically scaled up or
down, depending on the load.
Use-case specific versus agnostic generalists:
Companies either build their business models
around a specific industry and use case (e.g.
Accern) or leverage the fact that companies
across industries have a similar problem and
lack similar AI development resources (e.g.
MonkeyLearn, Levity).
What data types can be processed: AI isn't to
be confused with stew – just throwing a bunch
of data into it won't give you what you want.
Therefore, a key question is what data a
company focuses on in the first place – the
most important types being images, text,
documents, or structured (tabular) data.
Clarifai
DataRobot
Clarifai is an NLP and Computer Vision tool
founded in 2013 that offers an end-to-end
solution for modeling unstructured data for the
entire AI lifecycle. Image, video, and text
recognition solutions are built on an advanced
machine learning platform and made easily
accessible via API, device SDK, and onpremise. Boasts accurate and detailed results
with a fast API, they have some neat pretrained models on offer (people, vehicles, and
general detectors).
The DataRobot enterprise AI platform
democratizes data science and automates the
end-to-end process for building, deploying,
and maintaining AI. Founded in 2012, it’s core
focus is predictive models and is powered by
open-source algorithms and available in the
cloud, on-premise, or as a fully-managed AI
service.
CreateML
Since 2018, Apple has let developers deploy
custom ML models by using transfer learning.
The independent app allows users to build
models for object and activity detection,
image, video, sound, text, and tabular models.
Create ML leverages the machine learning
infrastructure built into Apple products like
Photos and Siri but also allows training with
custom data, train multiple models using
different datasets simultaneously.
Google AutoML
AutoML is the Google package star, and the
tool works much the same way as CreateML –
just on the cloud. The model package currently
includes Sight (Vision and Video Intelligence,
the latter in beta) and Language (NLP &
Translation) as well as structured data
(Tables) functions. AutoML overall manages to
cover a lot of ground already in no-code – but
once again, if you’re not a developer it’s hard
to operationalize.
Levity
Levity focuses on image, text, and document
classification and enables users to train
custom models on their use-case-specific data
– and is meant for businesses of any size.
Custom models and flows also include a
human-in-the-loop option, so users have full
control, as the model asks for input where it is
unsure – and will automatically learn from
interactions. Levity focuses on providing an
end-to-end solution and integrates with all the
tools people use on a daily basis.
Lobe
Lobe, a product by Microsoft, offers image
classification, with object detection, and data
classification coming soon. Lobe is a free,
private desktop application with a fair amount
of pre-trained solutions (e.g. Emotional
Reactions which allow your app to react to
different expressions allowing people to send
emoji reactions using just their faces).
The No-Code Automation Playbook | page 10
MakeML
ObviouslyAI
Founded in 2018, MakeML is a developer tool
used for creating object detection and
segmentation models. They have some great
tutorials out on detecting a number of touchpoints for sports games e.g. tennis and
football and segmenting potatoes for
something different - like chip production.
MakeML has a dataset store, with a ton of free
options, but also allows platform users to sell
and buy datasets from each other.
Obviously AI, founded in 2019 uses NLP
processing to perform tasks on user-specific
text data. Drag and drop your data as CSV or
integrate with HubSpot, Salesforce, or MySQL
(among others), pick your prediction column,
and it'll auto-build a custom ML algorithm and
you’ll end up with a prediction report. The
platform is especially useful for SMEs, who are
looking for a tool that chooses the right
algorithm for their needs.
MonkeyLearn
RunwayML
MonkeyLearn offers an all-in-one text analysis
and data visualization studio, for unstructured
text-based data to get topic, sentiment, intent,
keywords, etc. Features include automatically
tagging business data, visualizing actionable
insights and trends, and simplification
processes for both text classification and
extraction.
Integrates
with
Zendesk,
RapidMinder, and Google products, with a
whole bunch more coming soon. Also - in our
humble opinion - one of the best blog
resources out there when it comes to text
analysis.
RunwayML is a tool specifically designed for
creators and focuses on creative work
involving interacting with images, videos, text,
latent spaces, and segmentation masks and
supports motion capture, object detection
background removal, and style transfer. They
offer a Generative Engine – a storytelling
machine that automatically generates images
as you write.
Nanonets
Nanonets falls in the Computer Vision domain they have ready to use solutions for most
common document types, but offer a set up
for custom models as well. One of their cooler
solutions offers to build an ID card verification
model for any country, format, or language –
including perspective transformation, meaning
models that can work with tilted or angled
images.
Teachable Machine
Teachable Machine is another Google tool –
and a quick-and-dirty one. A web-based tool
that offers creating models to classify images,
sound, and body postures, and has an easy
drag-and-drop UI. You can teach your
machine by creating a data set with your
webcam, live in your browser, and run a
decent model with 30 images per class. They
run pretty cool projects with TM - check out
Project Euphoria here. The only downside,
really – you can also export the model file and
work with it someplace else, which can be a
bit painful for no-code building.
Use cases for no-code AI
“What can I do with it?” is arguably the most
common question in this space and there is a
good reason for it: By definition, the primary
user group of no-code AI consists of nontechnical people. They may know a thing or
two about AI but they are certainly not dealing
with the subject on a daily basis, let alone
code neural networks for a living.
As it turns out, the quickest way to grasping
the usefulness of AI as part of business
operations lies in studying a few use cases.
That’s when the “aha” moment usually
happens.
Note that some tools imply the use case by
way of how they have been set up (e.g. for a
specific industry or process) while others are
meant to be trained by the users with their
specific purposes. A few platforms offer both.
And naturally, there are different application
layers at play – classification, tagging,
detection, data extraction... the list goes on
and on – and so do the possibilities.
Nevertheless, there are things
to consider…
One of the myths in the no-code space is that
if you want to get to the stage of any solution
implementation, you have to lower your
expectations. The days when we had to choose
two-out-of-three between fast/cheap/good
are numbered, but expectations do have to be
managed.
The current no-code AI space shows that each
solution is intrinsically bound to the design of
the tool. Some practitioners point out that in
some cases, it is important to remember that
once you have developed an application on a
platform, you are linked to that platform for as
long as the application is running. In the
context of a PoC, this is not a problem, but in
the context of an application that is expected
to last, things can be different.
And even though no-code platforms mitigate
engineering and coding complexities, it is not
a magic tool that can be used for everything.
Instead, you should consider (as a processowner) some of the following questions:
1. What problem am I trying to solve? What
tasks make up this problem?
2. What is the level of project management
that we need?
3. What is the role of the tool/platform in the
company architecture?
4. Does the platform fit the problem needs?
5. Is using a no-code AI tool a strategic
choice that will drive value in the long run?
The No-Code Automation Playbook | page 12
What will the future bring?
Businesses are steadily moving towards nocode platforms for a number of reasons.
Partially due to the ripple effect on workforce
management, access to developers and
software engineers slows down project
delivery – and this is where technology can
add real value. Not only enabling your
workforce to deliver solutions but also staying
relevant and competitive in the current
landscape is the unicorn we all want to catch.
Research estimates that nearly 65% of
application development will be done through
low-code and no-code platforms as soon as
2024 – and no-code AI will play a significant
part in this. It is hard to see the logic of doing
things the traditional way when disruption of
current process management is possible and
widely available to everyone.
Nevertheless, useful AI applications require a
good use case, to begin with. Just having an AI
model is worth relatively little, regardless of
how powerful it is. But just as people have
found a new love for databases (thanks,
Airtable!) and Wikis (Notion), people are going
to pick up on the potential of AI. Just as nocode AI tools will mature, so will their users.
Thank you Luc Meijer (@NoCodeLuc), Andrew
Davison
(@AndrewJDavison),
Ryan
Myher
(@ryanmyher) and Bryce Vernon who runs a
Buildcamp Community for no-coders for your
contributions to this! This article has been written in
collaboration with our amazing team members
Arne Wolfewicz, Hanna Kleinings & Thilo Hüllmann.
The No-Code Automation Playbook | page 13
HOW TO TRANSFORM YOUR COMPANY’S
CHALLENGES INTO YOUR NEXT
PROMOTION WITH NO-CODE TOOLS
Philip Lakin
Co-Founder & CEO, Nocodeops
No-code is more than just a trendy phrase: It’s
a new avenue for tinkerers, entrepreneurs, and
makers to build applications on their own,
without needing technical support.
Because of its versatility, no-code has been
transforming not just small businesses, but also
enterprise-level companies. In fact, Gartner
predicts that nearly two-thirds of application
development will be low-code by 2024.
That said, no-code isn’t necessarily a “golden
ticket” to success, and a thoughtful, deliberate
approach is needed to gain real value. In this
article, I’ll explore my experience using nocode to solve company challenges and even
get promoted. I’ll then walk you through the
steps needed to do the same.
Using No-Code to 10x Growth
At the time, we were using a slow, inefficient,
paper-based sign-up solution. I realized that to
succeed in the fast-paced New York market,
we’d need something a whole lot more
efficient. However, I wasn’t a developer, and
getting developer buy-in can be a real
challenge, so I needed a no-code solution for
driver onboarding.
Breaking the challenge down into its core
components, I only needed a few things:
An interface for drivers to sign-up
A simple form
A database to hold records
A way to tie it all together
Fortunately, no-code offers simple solutions for
each of these components. Using ProntoForms,
Google Sheets, Zapier, and iMacros, I made an
app that our brand ambassadors could use out
in the field—with just an iPad—to onboard
drivers.
Successfully deploying no-code starts with
asking the question, “how can I build something
that’s valuable to my business?”
Beyond in-field ambassadors, we also
deployed self-serve driver onboarding stations
in our offices.
As an operations professional at Gett, an Israeli
Uber competitor expanding in New York at the
time, one of my key challenges was to recruit
drivers in the field.
This no-code strategy rocketed us from 3,000
drivers in New York to 30,000 in under a year
and a half. This incredible 10x improvement is
just a glimpse at the power of no-code.
The No-Code Automation Playbook | page 14
How No-Code Got Me
Promoted
After my time at Gett, I got recruited by
Compass, a leading, technology-forward real
estate brokerage. As Compass was growing at
a blazing speed across the US, they needed to
standardize real estate agent onboarding.
Given my experience in building and deploying
a no-code onboarding tool at Gett, I knew how
to hit the ground running.
The traditional ways of building onboarding
tools are slow, inefficient, and expensive. After
joining Compass, I already knew that no-code
was the way to go, but I’d also need the buy-in
of the rest of the national operations team.
I worked in a community-based fashion to
spread the idea of no-code, which ultimately
proved to be highly successful.
We set up a 30-day trial period to try out
various no-code onboarding tools, and then
voted on the best tool at the end of the period.
Ultimately, we decided on Enboarder, which let
us build a whole onboarding process with nocode, and customize it in any way needed.
This no-code solution was so simple that we
needed very little developer buy-in. In fact, the
only communication needed with developers
was for things like field and API updates, which
were just once a quarter.
5 Steps to No-Code Success
Let’s dive into 5 broad steps that anyone can
use to achieve no-code success.
1. Identify Business Challenges
The first step is to identify the right business
challenges.
The right business challenge, first and
foremost, is an opportunity to better serve
your customer, whether internal or external. At
Gett, for instance, we had the opportunity to
better serve drivers.
This opportunity should also be reflected in the
department’s goals. Naturally, a key metric at
Gett was the number of drivers onboarded. By
creating an efficient, seamless onboarding
application, we could clearly make headway
towards achieving that goal.
Another criterion is needing little to no
developer buy-in. Developers are busy people,
and all too often, they don’t have time to help
us non-technical folk and our internal needs.
Therefore, the challenge should be solvable
within the scope of no-code.
Finally, the challenge should be something
you’re truly interested in solving. Passion
drives curiosity, which is a huge element of nocode success.
The No-Code Automation Playbook | page 15
2. Find the Right Tools
Now that you’ve identified the business
challenge, it’s time to find no-code solutions.
There are a thousand and one places to look,
but here are a few to get started:
G2
Product Hunt
Capterra
Quora
This is where curiosity comes into play - you’ll
want to try out different solutions and see what
the right tool, or combination of tools, is for
your needs.
3. Make a Proposal
Now it’s time to get corporate buy-in.
Ultimately, you want to show that you could
figure out solutions on your own, and without
developer support. This means you’ll want to
talk to potential end users (internal and/or
external) to understand their problems, and
make internal alliances to gain support within
the company.
4. Get a Budget
Now that you have a proven business case, it’s
time to get the budget approval you need.
Fortunately, with no-code, the budget is likely
to be significantly smaller than it would with
traditional code-based applications, but it’s
still a key component of success.
Demonstration ROI based on time-saved and
what not fixing this process will cost the
business are helpful strategies in strengthening
your case.
I’m a huge advocate of building something
tangible, whether it’s a small feature, an MVP,
or even just a mock-up. When your manager
can see the solution, they’ll be a lot more likely
to support it.
The No-Code Automation Playbook | page 16
5. Go All-in
The final step is to go all-in, and really focus on
your no-code solution.
By creating a solution that solves real
problems, it’ll inevitably take up more of your
time, to the extent that you’ll practically
become a Product Manager for that solution.
Now that you have experience in no-code
solutions, you can look for similar ways to add
value - always keeping the business case in
mind.
From here, the opportunities are limitless.
Perhaps you’ll be promoted to a full-time role
in no-code operations, but you also have a
valuable skillset in implementing new solutions,
which would prove valuable in the search for a
higher-level job.
In any case, no-code is clearly a powerful way
to add value and take the next step in your
career.
The No-Code Automation Playbook | page 17
THE CENTRAL ROLE ZAPIER
PLAYS IN THE NO-CODE SPACE
Andy Wingrave
Chief Automator, andywingrave.com
Introduction
Today, the world depends on code to make the
world go round. No matter the kind of
streaming service you watch, an app you use,
or the emails you send to a client or family
member, someone behind the scenes has
written the code necessary to make all of this
happen.
Since code is crucial to today's modern world,
this leads to a significant problem. With many
companies looking to bridge the gap, low-cost
automation tools like Zapier are changing the
coding landscape.
As technology moves faster and faster each
year, it has become possible to create the
products you need without code. This is the nocode movement. Zapier is playing a central
role in empowering the everyday person to
build their business, projects, and even
products without having to know or even code
a single line. Nowadays, all we need to do is
tell a computer what it needs to do by putting
together visual blocks. This results in
automation which is Zapier's essential role.
The No-Code Automation Playbook | page 18
Many corporations and businesses are faced
with a shortage of software developers. Even
if they find them, retaining an excellent
software engineer is costly. Another significant
issue is that there aren't enough of them in the
market, especially when faced with new
technologies. One thing that is essential to a
business's survival is staying up-to-date on the
latest trends and technology.
As businesses become leaner and with
software developers in short supply, no-code
tools like Zapier shape the modern market.
While these developers will still be in high
demand for time to come, users who aren't
super tech-savvy turn to Zapier to complete
the automated solutions they need.
This is also helpful for many who can't afford
the high costs of programmers or coders to do
the work. Businesses often don't have the time,
and having a no-code solution like Zapier is
precisely what they need.
What you can automate with
Zapier
You can use Zapier to set something up so it
can run automatically. This automation can be
found everywhere you look. If you've ever
received a text alert or an email right after
signing for a business's newsletter, then you
have seen automation at work. Automating
your workflow with Zapier is as simple as
giving something a simple command. Even
something complex can be automated this
way.
Zapier will help you automate many of these
repetitive tasks without the need to write code.
You can even use Zapier to tell another app
what to do after a specific event. You can
automate any tasks you find yourself
frequently doing. Here are some examples:
Save new email attachments to a cloud
storage solution.
Push new Google Calendar events using a
workflow.
Get an automatic summary or digest of any
feed (sales invoices, Slack notifications,
Reddit mentions, Asana tasks…).
Integrate your to-do list with your
calendar, keeping track and calendarizing
unfinished tasks.
Share blog posts to social channels using
your blog’s RSS feed.
Collect and collate feedback and surveys
by integrating platforms like Typeform,
SurveyMonkey,
Salesforce,
Dropbox,
Google Forms and Trello to form
completely custom workflows from
automatically adding subscribers, through
campaign analysis.
Move information or data between apps.
This is especially useful when using project
management apps.
Automate your life and
business with Zaps
Drag and drop automation
without code
At Zapier's core is how it interacts with actions
and triggers. This is popularly known as a Zap.
It works similarly to a cause-and-effect model.
Typically, setting something like this up could
prove daunting, especially if your coding
knowledge is minimal.
Zapier's strength in the no-code sphere is its
ability to automate simple to complex tasks
without you having to learn or write a single
line of code. It helps you create customized
workflows within popular apps and other
services.
However, Zapier not only streamlines the
process but makes it more accessible. Creating
your first Zap to start your automation process
can be done quickly and efficiently. You can
test the Zap and even add filters. This means
you can add more actions to your Zap so you
can further streamline your process. You can
use filters also to limit these actions or make
your Zap work within a specific parameter.
By creating Zaps, Zapier uses simple triggers
to produce actions that will allow you to
automate tasks that would take too much time
otherwise. With its many subscription levels
available, you can easily find one that fits your
needs.
Zapier isn't your standard programming
software. One of its major pluses is that you
never have to need to know code to use it.
Zapier is a simple yet powerful macro editor
that will help you automate your basic tasks to
focus on what's essential to your business or
personal life.
Zapier has played a pivotal role in the nocode world. Its automation is revolutionary
and straightforward to use, with its defined
process that is used by companies worldwide.
It has a simple drag-and-drop interface with
dropdown boxes to help guide you in creating
the automation you need.
You'll find that learning how to use Zapier is
quick and has a minimal learning curve. Zapier
is perfect for you if you need automation but
can't afford the cost of a developer, or the
time it takes to implement.
Zapier makes launching your ideas and
automating your workflows easy, leading the
pack when it comes to no-code products and
services.
The No-Code Automation Playbook | page 20
HOW TO LEVERAGE AI IN YOUR BUSINESS
WITHOUT CODING KNOWLEDGE
Hanna Kleinings
Customer Operations Manager, Levity AI
First of all - can it be done?
The commercial use of artificial intelligence
offers tremendous potential to businesses of
any shape and size. According to PwC, AI is
estimated to add $15.7 trillion to the global
economy by 2030.
This is too much to ignore - whether you are a
small business or not. However, many people –
from corporate executives to small business
owners – have very little, if any, in-house
knowledge to build their own AI applications.
We cannot disregard the technology under the
hood: Proper AI systems require extensive skill
not only in data science but particularly in
software engineering and cloud computing. But
fear not - there is some good news: A few
companies have realized that much of this can
be neatly moved into a user-friendly frontend
for non-technical people.
We want to give you a small taste of what is
already possible today and how it can be
realized, without the technical noise that often
surrounds this matter.
You don't need to know how to
code to build an AI model
Most of us are already using AI in some form
every day. Be it a search engine, newsfeed, or
your phone's Face ID: There is some degree of
intelligence in it and the majority of it is
certainly artificial. But although we are all
getting used to these interactions, creating a
system that uses AI is something that still
happens on paper (or PowerPoint slides for
that matter).
In a similar fashion, websites could be visited
long before the general public could create
their own websites. Today, any person can
build their own website without a single line of
code. Companies like Wix, Jimdo, and
WordPress provide users with design templates
and guidelines. Instead of writing code, people
have to shift around boxes, insert pictures, and
write text.
These above-mentioned companies have
enabled people to leverage the full potential of
technology
without
extensive
technical
knowledge.
Building
websites
became
available to the masses.
The No-Code Automation Playbook | page 21
Local artisans now operate online-shops, the
small hairdresser from around the corner
offers online bookings.
What works for websites begins to work for
artificial intelligence systems as well. Similar to
website builders, specialized firms allow
people to build their own AI models without
code.
What used to be a domain for skilled software
developers and hobbyists is starting to become
mainstream. And in the same way, as not all
websites are built with website builders, we
don't claim that all AI systems can be built
without code. But we are more than happy to
give it a shot!
If you want to get your hands dirty, you can do
one of two things: Either directly get started on
our platform or dive deeper into the matter
first. The following three steps are a good
starting point for the latter.
1. Prioritize AI use cases
As with most things, the difficult part is getting
started.
We recommend you begin by brainstorming all
relevant processes in your company. Write
down everything that comes to your mind.
Don’t think about complexity yet! To give you
structure and inspiration, we built a template
that you can use to organize your thoughts:
Now, identify those processes out of your list
that are suitable for AI involvement. A suitable
process should fulfill the following three
criteria:
#1 The task is repetitive: You should use AI to
get rid of tedious daily tasks, not to find the
new strategic direction for your company.
#2 The task cannot be described by logical
rules: If it can, you don’t need AI - go for
robotic process automation instead.
#3 A skilled human can decide on the task in a
few seconds: AI excels at automating decisions
with clear input and related output. If a skilled
human needs to think hard about each
decision, don't try to automate the task (for
now).
If a process fulfills all three criteria it is
suitable for AI involvement.
Lastly, prioritize your list of suitable use cases.
Take into account two factors: importance and
complexity. Don’t overburden yourself with
something too difficult at the beginning! You
should begin with the most valuable option
among the processes that are easy to
implement.
What follows now is implementation. In a
nutshell, your action plan should look
something like this:
The No-Code Automation Playbook | page 22
1. Establish a first showcase solution
2. Get feedback from your environment (what
did work, what didn’t)
3. Spark the fascination of relevant
stakeholders (e.g. your boss, employees)
4. Continue with the next AI project, gradually
increasing the process complexity
2. Start a pilot project
Nothing holds you back to start leveraging AI
today - neither do you need to acquire any
technical knowledge, nor do you need to draft
your company's 2030 AI strategy first.
Instead, what you need to do is start building
your first pilot project. Implementation
certainly is the most important and exhausting
part. Even without code, it takes passion and
perseverance to give birth to your first AI
model.
But it will help you to learn the maximum
amount of information in the shortest time.
This is what you need, what your boss needs,
and, most importantly, what your company
needs.
Begin with the highest-ranking use case from
your prioritized shortlist. If you have followed
the previous step in this article, this is a
process that is suitable for AI involvement, has
a significant value for your business, and is
easy to implement.
Now, look for AI builders that help you to build
a custom AI solution without code for that
particular use case.
With these firms, you don't need technical
know-how to put your idea into practice.
Whatever your requirements are, there are
usually articles or videos that well explain
what you have to do.
Our blog, for instance, has a step-to-step
guideline on how you can build your first
image classifier in no time and without code.
You will soon have your first results. But it is
crucial to not stop here.
3. Learn and repeat
It is important to take your findings, learn from
them, and then repeat the whole cycle with a
new process. Think about the following
questions:
1. What were your key obstacles? How can
you overcome them next time?
2. What did key stakeholders (e.g. your boss,
your employees) think about the whole
process? In your next implementation cycle,
highlight the positive and improve on the
negative aspects.
3. What resources do you need to implement
future AI projects more effectively?
When trying to implement a technical project
as someone without a technical background,
these insights are crucial.
Now, continue with the next project on your
prioritized shortlist of use cases. This might be
a process a little bit more complex, but also
more value-adding.
Let’s summarize the key insights of this article:
The No-Code Automation Playbook | page 23
1. You don’t need to know how to code to
build an AI model. Similar to website
builders, there are firms offering custom AI
models
without
requiring
technical
knowledge.
2. Start a pilot project today. Don't spend your
time learning a programming language or
drafting your company's AI strategy - get
your hands dirty with a first prototype!
3. Learn and repeat as quickly as possible.
This is how you gain the maximum
information in the shortest amount of time.
4. Gradually increase the scope of your AI
projects. You will soon find out that you
have leveraged AI in your business without
writing a single line of code!
The No-Code Automation Playbook | page 24
INTEGRATING NO-CODE AUTOMATION
INTO SMES
Iulian Lupescu
Procesio
Why no-code?
As technology has evolved, the demand for
highly personalized software that one can
integrate into their business has exponentially
grown – and it’s no surprise.
The acute global need for software could not
be covered even in 50 years’ time using the
existing development human resources. The
symptoms of this global issue can be observed
through facts such as:
over 90% of SMEs are lagging behind digital
innovation.
over 1 million computer programmingrelated jobs in the US are expected to be
unfilled with similar figures in Europe.
81% of digital transformation projects fail,
suffer a major delay, or get scaled back.
98% of companies report challenges with
their architectures, with data silos topping
the list.
In this context, the biggest pain points for
companies are interconnection of data and
systems, data silos and process automation.
The solution to this lack of development
resources when facing such a high demand for
automation integrations may just be the same
as the answer to the long-standing ‘build or
buy’ dilemma. Some may claim that the best
way to effectively integrate software into your
business processes is through creating your
own automations.
It’s true that this would lead to a highly
personalized software - but the time, skill and
resources that must be invested to achieve this
might not be suited for small and medium sized
enterprises. From the opposite perspective,
others would lean towards off-the-shelf SaaS
products, but this solution may not be suited for
more complex processes that require a
personalized solution.
No-code platforms let you develop your own
workflows, this way integrating automated
processes into your business while making sure
that they fit your needs like a glove. No-code
means there is no need to hire large teams of
high-skilled engineers, this way not having to
face the issues posed by the limited availability
of software development resources.
Effectivity, scalability and accessibility come
together in no-code automation to bring a
solution to two longstanding issues in the SME
context.
The No-Code Automation Playbook | page 25
Automation as a solution for
sales professionals
SMEs can benefit from using no-code and lowcode software integration platforms to address
these issues by streamlining internal operations
without fully relying on expert developer
support.
This way, thanks to no-code automation
platforms it may be possible to close the gap
left between SMEs and the high demand for
highly skilled programmers.
It's not uncommon to believe that automation
and no-code platforms' availability is limited to
large businesses with unlimited resources, but
this couldn't be further from reality. Thanks to
the recent surge in PaaS, AIaaS and MLaaS
providers out there, businesses of all shapes
and sizes can now integrate automation into
their processes through one way or another.
Over the last few decades, automation has
become central to the effectiveness of most
business processes. If you don't believe this,
proof can be found when looking at what
happens when automation is completely absent
- hundreds of hours of unnecessary manual
work.
Take the example of a sales expert that
struggles to keep track and follow-up with all
the customer touch-points in her sales funnel.
She works with a CRM system which currently
does not make it possible to centralize all data
from prospects, sales leads and customers, so
she spends a lot of time assembling
fragmented information from different systems
and dashboards.
She approaches the CMO and CIO about a
possible solution. Although they are receptive,
her colleagues are reserved about the time it
would take to build this integration considering
the scale of data migration and complex
technical changes when switching from a
legacy system.
At this point, she could accept the limitations
and keep working with the legacy software, or
bypass that and use an external application
for (some of) her tasks.
This is an issue that many companies face as
they work to adapt to fast market changes and
integrate new software applications in their
internal operations. As shown in this example,
carrying your processes through a noncentralized system can drastically extend the
time you would need to invest in certain tasks.
A perfect solution for this issue would be
No-code automation is the solution to these
implementing a no-code automation platform
issues: with its implementation in your business
into her processes and migrating all data
you will be able to drastically cut mindless
points to this system, this way scalability
working hours with a quick implementation and
wouldn’t be an issue anymore and the
no need to hire large teams of highly skilled
effectivity of her processes would be boosted.
engineers.
The No-Code Automation Playbook | page 26
This option wouldn’t involve the
extensive time, costs and skills
needed to switch internal processes
to an in-house developed software
system.
Through outsourcing automation
services, the company would be
able to specify their needs to the
provider and this way get a highly
personalized CRM system that
would be more likely approved by
the CMO and CIO while enabling
the sales expert to optimize her
efficiency and centralize all data.
Through integrating automation in her
processes, this sales expert would be able to
bridge the gap left between a highly skilled
business professional and the demand for
highly skilled developers, all while meeting her
superiors’ needs and her own.
Key points to effectively
integrate automation in your
SME
Salesforce is one of the top apps used by sales
departments, therefore using integrations with
this platform can greatly help to eliminate
bottlenecks.
This platform enables sales professionals to
centralize all data, while offering the
possibility to run a multiplicity of customer
relationship management processes and
campaigns through the app – all through a
completely personalized system.
For instance, automating lead-to-cash
processes between finance and sales teams
can involve updating pricing information to
generate quotes, and notify finance teams
about new sales to start billing.
Many companies run this process manually
using back-and-forth emails or spreadsheets,
which ends up increasing the sales cycles and
possibly causing lost opportunities. The best
way to avoid this is by integrating automation
into your CRM processes, this way minimizing
the obstacles faced when aiming to centralize
all your data and processes.
An integration platform such as Procesio which
provides Salesforce connectors can automate
this information exchange so that teams
receive instant updates and maximize the
return on each transaction.
The No-Code Automation Playbook | page 27
Following the example of our sales expert
above, when using data such as web analytics
and product use, Salesforce doesn’t capture
all the touchpoints of the leads by default,
therefore a unified dashboard can better help
to know how engaged the users are with a
product or service – and this is when
integration platforms like Procesio get
involved.
Procesio is a PaaS provider that allows users
to create custom workflows and integrations
through no code and low code automations.
This platform enables completely tailored
processes that can be created through a very
intuitive drag-and-drop interface, it’s ideal
for, but not limited to, sales experts and offers
a multiplicity of integration options.
Coming back to the above-mentioned issue of
high demand and low resources in software
development, Procesio operates with the main
mission of closing the gap between the need
for developing products and the lack of human
resources.
It is through these automation platforms that
this issue can be effectively solved for SMEs.
Building your own apps through no-code or
low-code allows you to make sure that your
internal processes fit your needs like a glove,
without excessive time, effort or money
investments being necessary.
Integrations and scalability are essential parts
of any no code or low code platform, so when
looking to integrate these processes in your
business it is essential to look for the platform
whose functions and integrations best fit your
The No-Code Automation Playbook | page 28
business’s needs and will keep doing so as
your company grows.
Integrations and scalability are essential parts
of any no code or low code platform, so when
looking to integrate these processes in your
business it is essential to look for the platform
whose functions and integrations best fit your
business’s needs and will keep doing so as
your company grows.
One thing that we know for sure is that there is
a right platform for each SME out there – to
find what best works for you, you need to
know what your business’ needs are.
Thanks to these platforms, automation
becomes accessible for enterprises of all sizes,
reducing the need for custom-built internal
tools that require a high level of skill and time,
as well as eliminating non-custom software to
manage processes and store data as the only
alternative.
The No-Code Automation Playbook | page 29
WHY EVERY BUSINESS CAN BENEFIT FROM
AUTOMATION
Arne Wolfewicz
Growth, Levity AI
Business process automation is the key to
manifest your enterprise vision with minimum
supervision and maximum efficiency. Every
competitive edge matters in an ever-saturating
market no matter the size or type of your
business.
Many of your manually driven processes, such
as sorting and redirecting PDFs attachments,
prioritizing customer tickets, extracting
information from operational reports, etc.
demand precious time and energy. This
inevitably takes a toll on your productivity while
the rest of the industry is constantly innovating
to perform faster.
As a consequence, you can widen your profit
margins and redirect your funds to create more
value.
The beneficial effect on the bottom line,
particularly of AI-driven automation, could be
shown in a study by Accenture. According to
their data, automating or augmenting
processes with AI will lead to significant profit
improvements in a wide range of industries by
2035:
Future-proofing your
business: The benefits of
automation
1. Cost and time efficiency
As a decision-maker, automation needs to be
seen as a strategic investment with a long-term
footprint. Once you cover the initial
implementation costs, automating workflows
regularly leads to reduced labor hours, minimal
paperwork expenditure, and higher customer
satisfaction.
Share of profit increase per industry by 2035 (baseline 2017);
Source: Accenture and Frontier Economics
The No-Code Automation Playbook | page 30
2. Freeing up human capital & potential
In most organizations, human capital is that
extra something – despite or especially
because of increasing digitalization.
Automation can be the great liberator of
human capital in your organization by freeing
them from tedious work. As a result, managers
can manage their resources much better and
assign high-value tasks to your employees.
To put this in numbers, WorkMarket reported
that 53% of employees acknowledge that they
can save up to two work hours a day through
automation, while 78% of business leaders
state that automation can free up to three
work hours a day.
This leads to about six weeks of time per year
for regular employees and nine additional
weeks of productive work time on
management level.
3. Lower employee turnover
High turnover usually occurs in positions
requiring people to impassively perform
repetitive tasks. When you free your employees
from mundane processes and assign them
creative and engaging activities, it boosts
employee satisfaction. Satisfied employees are
high performers and more committed to
rallying for your business objectives for longer
stretches of time.
You may know best about its reverse, where a
high employee turnover not only causes a drop
in employee morale but also incurs significant
expenses for replacement.
4. Minimize human error
The various effects of human errors can range
from embarrassing email-typos to data
breaches that can cost millions.
According to the market intelligence firm IDC,
human errors in handling and processing data
cost the average multinational corporation an
estimated $62.4 million a year. And even
though this may be far greater than what your
business is facing, it sends a clear signal.
Mistakes are human. Even if we have the skills,
experience, and willpower to conduct a
routine task, it is likely that we will make a
mistake at some point. Automating your
workflows also reduces possibilities for human
error.
Machines, on the other hand, work precisely
according to pre-specified methods and
without fluctuating attention. Once you
thoroughly configured the automation set-up,
it will deliver consistent results.
Systems using AI automation are similar in
nature: Some applications require extensive
tuning but achieve performance levels far
greater than human beings could ever reach.
The No-Code Automation Playbook | page 31
5. Greater customer satisfaction
A recent survey by Capgemini found that 730
out of of 1,000 surveyed companies affirm that
automation can boost customer satisfaction.
Early adopters who started using automation
technology to refine their customer services
reported a 19% increase in operating margins
over a five-year period.
How so? You may already be collecting lots of
information on your customers and putting
them to great use. Machine learning can also
be used to work with data - that isn't
currently recorded in a standardized format.
Be it inquiries via email or product usage – it
can be effectively collected, analyzed and
interpreted automatically.
The machine learning
intervention: Paving the path
to workflow optimization
The path forward
Irrespective of the size or nature of the
business, companies around the world are
recognizing that automation is their passport
to productivity and profitability. And there is
every reason to do so: new tools are making
setup, use and integration of such technologies
comparably cheap and – probably more
importantly – accessible for a wider audience.
We are ready for the dance. We hope you are
too!
Business automation is a simplicity-centric
intervention meant to make human
participation more meaningful and guarantee
operational excellence in the long run.
Traditional automation, particularly Robotic
Process Automation ("RPA") is centered around
rule-based processes and analysis of
structured data at best. However, most
processes do not follow simple rules and are
often triggered by unstructured data, to begin
with – documents, images, messages.
The No Code Automation Playbook | page 32
THE FUTURE OF NO-CODE APPLICATIONS
Mariam Hakobyan
Co-Founder & CEO, Softr.io
For decades, people have been able to operate
computers without writing a line of code. Now,
a similar transformation is happening for
people who want to build software with the
explosion of no-code technology.
While the term “no-code” is relatively new, the
industry is already taking off and is projected
to hit over $43 billion in market cap by 2023.
But the recent explosion is the result of decades
of hard work and development that cannot be
ignored.
A brief history of no-code
In Phase 1 (the 1990s), programs like Word,
Excel, and Photoshop were built so that endusers didn’t need to know code to use
Microsoft's & Adobe's core feature set.
In Phase 2 (the 2000s), new players
democratized who could use – and even build
on – computers. WordPress launched in 2003,
revolutionizing how people built their own
websites, with a drag & drop platform,
including later, the revolutionary world of
WordPress plugins.
In Phase 3 (2010-present) platforms like
WordPress, Salesforce, and Shopify continued
to upgrade their core systems to make it easier
to build and customize their platforms without
code. App creators on these ecosystems also
focused more heavily on additional features
and customizability.
But another innovation happened: no-code
platforms started popping up to empower
people to build entire apps without code.
Instead of relying on plugin developers to make
the feature you needed, you could build it
yourself. Even API connections got the no-code
treatment from no-code experts startups like
Zapier.
No code is here to stay
As the world shifts to digital, people are forced
to adapt. Businesses become leaner, and run
increasingly online. Especially in COVID times,
the survival of these businesses depends on
how fast they can adapt.
Due to a huge shortage of engineers, it
becomes prohibitively expensive to hire an
engineer or an external agency to build an app
The No-Code Automation Playbook | page 33
for your company. Even vertical software
solutions like Hubspot, Salesforce, etc remain
out of reach for many lean SMEs.
Now, building an application is no longer
solely a programmer's task. Using code-free
technologies, business owners, non-tech
employees, designers and entrepreneurs can
create applications without coding knowledge.
How no-code application
builders like Softr work
The earliest iterations of no-code builders
helped with wireframes and prototypes. They
were also very technical and difficult to use.
There is a huge gap in the market — the
current tools are either too basic (only letting
you build static websites) or too complex for
the average person. So we set out to build a
platform that’s easy to use, yet powerful and
rich in functionality.
Our solution is Softr, an all-in-one SaaS
platform for SMBs and creators to build,
manage and run their business online without
code. It’s even earned us the moniker ‘the
LEGO kit of the web’.
At its core, Softr's units are the building blocks.
Each building block represents a logical piece
of the application, including frontend, business
logic, and backend.
This means anyone can build a professional,
robust web app with out-of-the-box
memberships, payments, search, filtering, roles
& permissions, using Airtable as your data
source.
You can build B2B & B2C applications like
client portals, internal tools, marketplaces,
online communities, and resource directories.
Every application built with Softr is fully
responsive, too.
The No-Code Automation Playbook | page 34
What does the future hold?
The real power of no-code is not that it’s a
new way to build apps. It’s the fundamental
shift in who can build an app or website.
Coding has a steep learning curve – you
literally have to learn another language just to
build a simple calculator function, let alone a
complex and response application or website.
No-code has reached a tipping point where
powerful website and web app builders can
mimic the work of a small team of developers.
And the potential is just getting started:
innovators in the space are working on making
no-code builders not only more powerful but
more intuitive and easier to use, which will
truly democratize access to building solutions
with technology.
The No-Code Automation Playbook | page 35
BOOK A DEMO
Interested in learning more about how Levity
can bring you closer to your organization's
goals - and free up employee time to do
more meaningful work?
We work with image, document and text
classification, using machine learning to go
beyond workflow automation.
Tell us your use case and we would be
delighted to walk you through our no code AI
software!
CLICK HERE