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Automate content generation, design prototyping and data synthesis, and remove slow manual steps from your workflows.
Generative AI · End-to-end partner
Generative AI Development Company: one partner from use case to live system
We take generative AI projects through the full life cycle: validating the use case, choosing the right approach, preparing the data, building and deploying the solution, and keeping it performing after launch. You work with one team from the first assessment to ongoing maintenance.
- Use cases validated against your business goals
- The most efficient, low-maintenance approach chosen
- Models maintained and improved after launch
- 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 generative AI delivers for your business
Generative models create new text, images and data. We apply them where that changes cost, speed or customer experience.
Make better-informed decisions
Analyse large volumes of data to surface patterns, trends and predictions that are not obvious to human analysts.
Personalise at scale
Generate tailored recommendations, product suggestions and content based on individual preferences and behaviour, to raise engagement and loyalty.
What we deliver
Our generative AI services
Six services that cover the whole path, from choosing an approach to running and improving the solution.
- 01
Generative AI consulting
Generative AI evolves quickly and there are many ways to build a solution. We help you choose the most efficient, cost-effective and low-maintenance one for your requirements.
- 02
Generative AI development
Once the challenge is clear, we build a working generative AI product or service using deep learning, probabilistic programming, NLP and neural networks, and deploy it across the platforms you need.
- 03
Integration and replication
We integrate and replicate generative models across your applications, for tasks such as content production, sales forecasting and personalised product suggestions, and check that outputs meet your specifications.
- 04
Automation and optimisation
We automate repetitive content tasks and optimise the algorithms behind them, so your systems generate content at scale with consistent quality and faster turnaround.
- 05
Maintenance and support
We keep models producing high-quality output through continuous data and algorithm training, and identify and resolve defects before they affect your operations.
- 06
Generative AI research and development
We explore, test and refine new generative techniques, so your projects benefit from the latest advances rather than yesterday’s methods.
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
Healthcare · Computer Vision, Generative AI
Medical image translation between tissue stains for a pharma company
Reusedone disease classifier across stain reagents
An AI component that translates histological images from one stain domain to another, so existing software and machine learning models can be reused across all reagents.
Read the case study
Custom LLM chatbot with document references for a consulting firm
In-house LLM no reliance on third-party LLM services
A private, hosted chatbot built on a custom large language model, giving a consulting firm answers with source references while keeping full control over its data.
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.
NLP chatbot for centralised meeting scheduling
3,000 man-hours saved per month
A natural language processing chatbot for a centralised meeting scheduling system that automated the process and reduced the number of human operators needed.
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
“Overall, our experience with AI Superior has been extremely positive, and we have been highly satisfied.”
Delivered a highly specialized AI chatbot with custom AI logic for a foundation supporting children and young adults.
“They delivered an extra module that we were not expecting but turned out to be very useful.”
Research and custom software development applying generative adversarial networks for a pharmaceutical company with 5,000+ employees.
“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.
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
Use cases by industry
Generative AI across industries
Examples of where generative models create value in each sector.
Healthcare and medicine
Generative models support diagnosis, treatment planning and the search for new medications.
- High-resolution images for diagnosis and surgical planning
- Novel molecular structures for drug development
- Health risk prediction from patient data
- Personalised treatment recommendations
Finance and trading
Models analyse large volumes of market and transaction data to reduce risk and inform decisions.
- Market anomaly and pattern detection
- Fraud detection
- Transaction monitoring
- Trading strategy optimisation
Entertainment and gaming
Generative AI supports content creation and character design for more immersive experiences.
- Game levels, landscapes and characters
- Special effects and realistic scenes
- Content for artists, designers and musicians
Architecture and construction
Models help architects and engineers explore designs and reduce resource waste in planning.
- Design alternatives
- Structural performance simulation
- Layout optimisation
Retail and fashion
Generative AI changes how retailers interact with customers and plan inventory.
- Personalised recommendations
- Trend forecasting
- Virtual try-ons
- Inventory optimisation
Manufacturing
Generative AI improves product design, quality and production efficiency.
- Product design for launches
- Production process optimisation
- Supply chain management
- Quality control
Marketing
Generative AI helps marketers reach the right people with the right message at the right time.
- Personalised messaging
- Content creation
- Audience targeting
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 a generative AI development company provide?
The full life cycle: consulting to choose the right approach, development of the model or product, integration into your existing systems, replication of models for new applications, automation and optimisation of content workflows, research into new techniques, and continuous maintenance so the solution stays accurate and up to date.
How do you run a generative AI project?
We validate the use case against your business goals, gather requirements and define scope, then prepare and clean the data. Next we select the technology and model, design a scalable architecture that fits your existing systems and define evaluation metrics. We then develop and test in continuous cycles, deploy into your infrastructure and support the solution after launch.
How accurate are generative AI models?
It depends on the model, the complexity of the task and the quality of the training data. Language models can produce coherent, relevant text but can also produce inaccurate statements. That is why we define precise evaluation metrics before development and monitor output quality after deployment.
How is generative AI different from traditional AI?
Traditional AI relies on algorithms and pre-set rules to analyse and process existing data for specific tasks. Generative AI learns patterns from existing data and uses them to create new content, such as text, images or synthetic data.
Where can generative AI be applied in our business?
Common applications are content creation and summarisation, document and report generation, process automation, personalised recommendations and messaging, context-aware translation and localisation, enhanced chat and search, and synthetic data to train other machine learning models when real data is limited.
How long does it take to develop a generative AI model?
It depends on the complexity of the project and the size of the training data set. Generally a solution takes from several weeks to a few months. We plan the timeline around your requirements and give you an estimate once we understand the project.
What does generative AI development cost?
Cost depends on the complexity of the solution, the project scope and the problem you are solving. Because every project is different, we scope it with you first and then provide a quote tailored to your project.
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.