Focus on the highest-value initiatives
Use cases are ranked by feasibility, impact, data availability and resource requirements, so you prioritise the ones with the strongest return.
AI consulting · Use case identification
AI Use Case Identification that shows where AI will pay off
Most organisations have more AI options than budget. We assess each candidate use case for feasibility, data, skills, legal risk, timeline and cost, then prioritise with you the initiatives that bring the most value to your business.
- High-impact AI opportunities specific to your business
- Each use case checked for data, skills and constraints
- A prioritised shortlist agreed with your team
- 57% of our team hold a PhD
- German company, working under the GDPR
Discuss your project
5.0 18 reviews on Clutch Go Global Awards winner
Trusted by enterprises, scale-ups and non-profits
What you gain
What a structured assessment gives you
A systematic process replaces guesswork, so investment goes to the use cases that can deliver.
Know what is feasible before you build
Technical requirements, data quality and technical constraints are checked up front, before a project absorbs time and budget.
Plan with realistic timelines and costs
Each shortlisted use case comes with an estimate covering development, testing, integration, and ongoing maintenance and support.
What we deliver
Our use case identification process
Eight steps take a long list of options to a small set of feasible, prioritised use cases.
- 01
Technical requirements
We assess what each use case demands, from problem complexity to the data, computational resources and AI techniques it needs.
- 02
Data availability
We check whether the necessary data is accessible and evaluate its quality, volume, variety, privacy, security and governance.
- 03
Skill and expertise requirements
We define the skills needed to develop and deploy each use case, and compare them with the expertise you already have in-house.
- 04
Ethical and legal considerations
We examine privacy, data protection, fairness and bias implications, so proposed use cases comply with relevant rules and guidelines.
- 05
Technical constraints
We identify limits that affect feasibility, such as computational power, storage capacity, network infrastructure and software dependencies.
- 06
Timeline and costs
We estimate the time and cost of development, testing, integration, and ongoing maintenance and support for each use case.
- 07
Prioritisation and selection
We rank use cases by feasibility, impact, data availability and resource requirements, and select the most viable options together with you.
- 08
Strategy, validation and prototyping
Once use cases are selected, we draw up an implementation strategy and support you through validation and prototyping.
Not sure which of these you need? Describe the problem and we will recommend the approach.
Discuss your projectCase studies
All case studiesResults we delivered for our clients
Finance · NLP
Semantic company search for private equity deal sourcing
1 weekof analyst work saved per new niche market
An end-to-end NLP solution that lets private equity funds and venture capital firms find and cluster relevant companies by meaning rather than by industry code or keyword.
Read the case study
Candidate scoring and matching for an online recruiting platform
800 man-hours of expert scoring saved per month
Automated candidate scoring and candidate-to-company matching for an online recruiting platform, replacing manual assessment of technical skills.
Telematics-based driver scoring for usage-based insurance
Per trip driving score and personal discount
A deep learning model that analyses telematic data from drivers’ phones to detect driving behaviour, score each trip and calculate personalised discounts and safe-driving recommendations.
Drone-based construction debris detection for a city municipality
40% lower average inspection costs
A drone-based application that detects and reports 25 types of construction debris, automating construction site inspections and saving 320 man-hours per month.
NLP skill gap analytics for a science and technology company
~10,000 man-hours saved
An interactive NLP tool that assesses employees' skills, compares skill profiles and identifies skill gaps between business-critical staff and their potential successors.
Why AI Superior
Research-grade AI, delivered like a product company
Many vendors can build a demo. Making AI work reliably on real data, inside real business processes, is the hard part, and it needs a different kind of team.
01
A research-led team
AI Superior was founded in 2019 by AI researchers with published papers and patents, and the whole team works to that research standard.
- PhD57%
- MSc28%
- BSc15%
02
Built to reach production
Every project is de-risked in stages, with a go/no-go decision at each milestone, so budget only goes into approaches that have worked on your data.
4× our proof-of-concept success rate compared with the market average
03
A complete team from day one
Strategy, models and software are designed by one team, so nothing gets lost in hand-overs between vendors.
- Product AI product owner, business analyst, project manager
- Data Data scientists, ML engineers, BI analyst
- Development Software engineers, QA, DevOps
04
Your data stays under control
When data must not leave your organisation, we build on private, self-hosted models instead of third-party AI services.
- GDPR, German company
- Self-hosted LLMs
- Transparent methods
Our team
The experts behind your project
Your project is led by senior data scientists and engineers with research backgrounds, supported by our product and development teams.
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Dr. Ivan Tankoyeu CEO PhD in Computer Science. Recognised by the IEEE GRSS Society, winner of the Global AI Hackathon 2017, Kaggle TOP500 data scientist (2014).
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Dr. Sergey Sukhanov Advisor PhD in Machine Learning, data scientist since 2013. Publications, patents and 30+ implemented AI use cases; several IEEE awards.
Client reviews
5.0 Rated 5.0 by the people we build for
18 verified reviews on Clutch
“I appreciate their approach, expertise, and the quality of information they provide.”
AI and machine learning consulting to identify the right use cases for a web design and graphics company.
“They are not only great theoretical experts, but also deliver with their awesome hands-on skills.”
“I would be more than happy to speak to anyone about how much of a rock star you guys are.”
How we work
A staged AI project life cycle
Every stage ends with a result you can check, and you decide on the next one only after seeing the previous one work. You keep control of scope and budget.
- Estimate before you commitYou see scope and expected results before the build begins.
- Go/no-go after every stageEach stage ends with a result you can check and a decision on the next step.
- Risks reported openlyWe share risks and opportunities as soon as the analysis shows them.
- Go / no-go decision
Discovery
We work through the business problem with your team and define the direction of the solution.
You get: Scope, approach and a high-level estimate of effort and expected results
- Go / no-go decision
Data and feasibility
We get to know your team and data and check whether AI is the right tool for this problem.
You get: A data assessment and a clear feasibility verdict before any build starts
- Go / no-go decision
Proof of concept / MVP
We start small, using the data already available, to test the solution in practice.
You get: Measured results on your own data and a basis for the investment decision
- Go / no-go decision
Integration and scaling
We integrate the solution into your existing systems, fine-tune the models and adjust them where needed.
You get: A solution running inside your processes, compatible with your data and systems
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Evaluation
We review the results with you and make sure they are read correctly.
You get: What the solution delivered and where to improve next
Awards and recognition
Ranked among the top AI companies
Recognised by international business awards and by independent B2B platforms that rank companies on verified client reviews.
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Top Artificial Intelligence Company Germany 2026 · Clutch -
Top Machine Learning Company Germany 2026 · Clutch -
Top Computer Vision Company Germany 2026 · Clutch -
Top Generative AI Company Germany 2026 · Clutch -
Go Global Awards Winner 2021 · International Trade Council -
Best Data Science & AI Service Provider, Europe 2021 · German Business Awards -
Top Artificial Intelligence Company 2023 · Clutch -
Top Machine Learning Company 2023 · Clutch -
Clutch Champion Fall 2023 · Clutch -
Clutch Global Fall 2023 · Clutch -
Top BI & Big Data Company Germany 2023 · Clutch -
Top IT Services Company Germany 2023 · Clutch -
Top Artificial Intelligence Companies 2023 · TrueFirms -
Top Machine Learning Companies 2021 · Techreviewer -
Most Reviewed IT Services Companies Germany · The Manifest
What does AI use case identification involve?
We analyse your business processes to find where AI can improve efficiency and customer experience, assess your readiness for AI, and evaluate each candidate use case against technical requirements, data availability, skills, ethical and legal considerations, technical constraints, timeline and cost.
How do you prioritise use cases?
By feasibility, business impact, data availability and resource requirements. The final selection is made together with you, so the shortlist reflects both the analysis and your business priorities.
What do you check about our data?
Whether the data each use case needs is accessible, and its quality, volume and variety. We also look at privacy, security and governance, because a use case that cannot use its data lawfully is not feasible.
We are not sure where AI fits in our business. Is this the right starting point?
Yes. The service is designed for companies that are unsure of AI’s potential for their business, do not know where to start, or have several options and need help prioritising them.
What happens after the use cases are selected?
We draw up a strategy for implementation and support you through validation and prototyping. A small-scale proof of concept tests feasibility and impact before a larger investment.
Do you also consider whether we have the right people?
Yes. We evaluate the technical skills each use case requires against your in-house resources and identify where specialised expertise is needed, whether from new hires or an external team.
Start your project
Tell us what you want AI to do for your business
Share a few details and our AI team will take it from there. Here is what happens next:
- We review your request and reply by email.
- A call with an AI expert to understand your problem, data and goals.
- A clear recommendation: the approach we suggest and a high-level estimate.