AI development
the strategic way

Unlock the hidden potential of data to drive tangible business results – and do it faster than you’d expect

Let’s talk about AI for your business

Your AI-driven digital transformation

Previously available exclusively to tech giants, artificial intelligence is now making its way into more organizations’ processes. Now democratized, the technology can be used by all businesses to modify customer experiences, meet the changing needs of the market, soothe the pains of employees relying on guesswork – bring real value.

artificial intelligence (AI) for digital transformation

But AI development takes loads of time and money…

It does. Full Artificial Intelligence adoption can take years and eat up whatever there is in your budget. It’s an R&D project, and as such it has both the potential and risks. Studies show that many AI projects fall short of expectations and never deliver the value that was promised – it’s the problem of as many as 8 out of 10 AI implementations!

It all sounds scary, we’re aware of that. There’s this pixie dust (in other words: Artificial Intelligence) that can solve your business problems, but so far, getting hold of it feels nearly impossible. Unknown timeframe, unknown budget, unknown results. How’s that for working with data, when all is unknown?

It’s not all that dark, though. So why don’t we take a small step first, and make AI a strategic move, and not a leap of faith?

Can AI be done differently?

It can, and it should.

What if we told you that it is possible to check whether your AI will pay off? And do so without wasting months or spending hundreds of thousands of dollars. There is no point in developing something that won’t work. So before you commit, let’s challenge the idea of Artificial Intelligence being your problem solver.

Ready for AI adoption?

Let’s talk

about your project!

To adopt Artificial Intelligence successfully, you need to start smart:

01
Learn how to work with R&D projects
AI projects are much like experiments - and in order to get on board with AI adoption, you need to be ready to test ideas, and let some of them fail
02
Gain understanding of data-driven culture
Don’t underestimate the human factor of AI - it’s created to augment your team, so you need to get them ready for being more data-driven and AI-friendly
03
Find just the right use case
Identifying the proper use case is one of the common bottlenecks to successful AI adoption - don’t let it happen to you! Find the model that will solve your most burning problems
See how these companies benefited from approaching AI in a more strategic way:
The World Bank logo - web application development, AI development
4com logo
boeing logo web app development

Setting business up for AI adoption

In less than one month, we validated the idea of using AI to improve sales rates in a British telecom company – with over 91% success probability!

View the Case Study
artificial intelligence adoption - proof of concept

Reducing customer churn by more than 20%

After full rollout of the AI-based system, our client ended up with more than 10x return on their investment.

View the Case Study
artificial intelligence reducing churn in telecom

10 weeks to build a course recommender system

An AI-based platform recommends the right courses to support employees’ development at one of the world’s biggest financial institutions.

View the Case Study
ai to boost human intelligence

Step 1
Sprint

How did they do it? With the AI Sprint

The AI Sprint is a short-term, fixed process where we help you discover the potential for Artificial Intelligence in your organization, identify the most promising use cases, build the base for your data strategy, test and assess the solutions to show you what they’re worth.

How do we do that?
The talk

First things first: we start with a talk. It is crucial to communicate well in AI projects, at every step of the way. It’s crucial from the very beginning to make sure everyone has a full understanding of the business, the pains, the hopes, and the assumptions.

The match

Knowing your operations and your struggles, we can list Artificial Intelligence solutions that have the best chances to bring you quick wins and open up the path to company-wide AI adoption. We find the right algorithm for you looking at your objectives, requirements, and data.

The exploration

The data science team performs the AI research – exploratory data analysis (EDA) – to discover patterns, spot anomalies, and test hypotheses. With the results, we have a full picture of what the data represents and how it can be used in the most efficient way.

The test

There’s the moment of truth. We test various machine learning algorithms to find the best fit. We assess the probability of successful implementation of the selected solution, and we get you ready for the next steps with tailored recommendations for your AI journey.

After AI Sprint, you will get:

AI Sprint report how to implement artificial intelligence
Detailed AI Sprint
report

Convince your stakeholders that Artificial Intelligence is worth the shot with the findings and results of the AI Sprint.

ai research - artificial intelligence data strategy
Custom data
strategy

Organize relevant elements of AI adoption and standardize the way your company will work with AI projects.

recommendations for artificial intelligence / machine learning adoption
Recommendations
for AI adoption

See how to move forward strategically to make the most of AI adoption.

artificial intelligence machine learning proof of concept for ai
Proof-of-Concept

Get evidence that Artificial Intelligence can (or cannot) deliver tangible value to your organization.

We were really hyped up with the workshops and the method. We appreciate the input of the AI team and the involvement of the team leader, which made us feel taken seriously. It was very valuable. The way of working in data projects is not obvious, but Neoteric helped us choose the right method.

Frederick Himperich, COO & CTO at Traffective

Step 2
AI Development

The PoC has shown you whether the idea is viable but also gave you a taste of what it’s like to work with external data scientists. The base of your data strategy and recommendations lay the groundwork for a successful, strategic implementation.

 

Now it’s time to bring the idea to life.

 

Your AI Sprint has tested a variety of models that can solve your problem, and at the end, you see which AI-based solution performs best. No matter if it’s a recommender system to suggest your customers the next purchase, predictive models to assess the risk of churn, dynamic pricing to increase your margin profit, speech recognition to improve customer service, or some other solution utilizing machine learning, we have a process that will help you bring it to life.

machine learning / ai development: predictive analytics
Predictive analytics

Gain valuable insights about future events and use Artificial Intelligence to predict e.g. customer churn or employee turnover to be more proactive.

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machine learning / ai development: recommender systems
Recommender systems

Give your customers personalized, AI-based recommendations of products or content to boost their engagement, improve customer service, and increase sales.

read more
machine learning / AI development - dynamic pricing
Dynamic pricing

Adjust your prices when needed – automatically. Dynamic pricing allows for a higher margin and better conversion rates.

read more
artificial intelligence development: scoring machine learning algorithms (AI)
Scoring
models

Assess the value of items using AI, evaluate the probability of conversion (lead scoring) or verify credit risk (credit scoring).

machine learning artificial intelligence development: natural language processing
Natural language processing

Handle customer queries more efficiently with the help of NLP-powered chatbots. Gain more understanding of users with sentiment analysis.

other artificial intelligence machine learning solutions: deep learning, neural networks, cognitive computing
...or something
else

Artificial intelligence is not limited to the models described here – and it’s not about what model seems to be the right fit, but what proves to be the right fit. Whatever your right AI model is, we’ll find it!

Ready to choose your AI weapon?

Let’s talk

about your project!

The custom AI development process
Scoping session

What does your project need? A scoping session is a great starting point for the AI development process – it help you list all the requirements and jobs to be done. Thanks to that, we can build a team tailored to your needs: including data scientists, software development engineers, designers, or a Scrum Master, estimate the time to deliver, and manage the work efficiently.

Project kickoff

With the team selected and educated on your project requirements, it’s time to start the work! During a kickoff meeting, you’ll get to know the team a little better and discuss all the essential points of your collaboration in detail.

AI Development

Data science projects are managed slightly differently since the models have to learn, but our teams are always loyal to the Scrum methodology. Don’t forget about your role in the development! It’s important for you to participate in the process – go to “Your AI development team” to see why.

Launch

The AI model has been trained and tested, your team is learning how to use it right, so it’s time to go live. Depending on the path you’ve taken (stand-alone AI-powered solution or model integration into an existing system), the steps towards launch can be different. And once it’s live, all that’s left is to use AI to the fullest!

Your
AI Development Team

AI development involves the work of the data science team, software development engineers, and scrum masters, but it also includes you at the heart of the project – it is all done in collaboration with you and your team to meet all expectations. Artificial Intelligence is not just the algorithms – it’s how it works within your organization, including getting onboard with data-driven culture.

Your AI development team may include these roles:

ai development team: business domain expert
Your Expert

Your domain expert (e.g. head of marketing) or an engineer. Or both. The people who will later work with the model in their daily tasks should participate in the process, too.

computer science machine learning AI development team: ai team leader
AI Team Leader

Watching over the process, questioning assumptions, suggesting ever better solutions to problems. A person who will consult you if needed.

computer science machine learning ai development team: software engineers
Software devs

Data science projects aren’t limited to data work. Software engineers will build your dashboards, interfaces, or a whole new AI-ready program to allow for easy use of the model.

Artificial intelligence machine learning development team: scrum master
Scrum Master

A person who makes sure the team’s work goes as smoothly as possible and facilitates communication between the AI development team and your team.

computer science machine learning AI development team: data scientists
Data Scientist

An absolute must in any data science project. The person who’ll take your data and bring it back to changed like it’s had a makeover.

computer science machine learning ai development team: UI/UX designer
UX / UI Designer

Need a pretty dashboard? Want to build a full app? The designer will help you turn your ideas into reality that is pretty, usable, and intuitive.

artificial intelligence development team product owner
Product Owner

The decision-making person responsible for the success of the project – and involved in the process to accept increments, ask and/or answer questions, specify needs.

artificial intelligence machine learning development team po proxy
PO Proxy

The PO proxy is a person who will support you in defining requirements, communicating your needs clearly, and maximizing value derived from the product.

Your
Strategic Partner

Developing your AI solution can be difficult from the very beginning, and that’s exactly why you might need help kicking off. You might need advisory on the use case, technical know-how to understand what’s achievable, or development power to get the project running.

At Neoteric, we address these needs, building teams adjusted to your requirements, listening to your needs, and making sure communication is always honest and clear. This way, a strong partnership is built: our team works alongside yours to develop an AI-powered solution living up to every expectation.

See where Artificial
Intelligence will take you

Book Your AI Sprint

Looking for other Services?

Check out other areas that we can help you with. No matter what your challenge is, we are here to help you.

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