Accuracy in your domain
A model built with your domain knowledge understands the context of finance, healthcare, legal or your own field, not just general language.
Custom LLMs · Built for your domain
Large Language Model (LLM) Creation Services: a model built around your business
When a general-purpose model is not precise enough for your domain, or you need full control over your data, we create a custom LLM. We design the model, prepare the data, train and optimise it, and deploy it in the cloud, on-premises or in a hybrid infrastructure.
- Domain-specific accuracy for your industry
- Full control over your data and your model
- Deployed in the cloud, on-premises or hybrid
- 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
Why build your own LLM
A custom model gives you accuracy, control and performance that a generic one cannot.
Control over your data
Privacy-first design with encryption, access control and regulatory compliance built into every stage of model creation.
Efficient in production
We tune parameters and computational resources for faster inference, reliable output and sensible running costs.
What we deliver
Our LLM creation services
Every stage of building a proprietary language model, from the first dataset to ongoing support.
- 01
Custom LLM design
We design models around your business objectives, with domain-specific knowledge and multilingual support where you need it.
- 02
Data collection and preprocessing
We source, clean, preprocess and structure large datasets, because model quality starts with data quality.
- 03
Model training
We train the model with current techniques, balancing speed, accuracy and cost-efficiency.
- 04
Fine-tuning for your use cases
We refine the model’s behaviour for specific tasks to improve accuracy and response speed.
- 05
Evaluation and optimisation
We evaluate performance rigorously, adjust parameters and optimise compute for faster inference and higher reliability.
- 06
Security and compliance
Encryption, access control and compliance with the regulations of your industry are part of the design, not an afterthought.
- 07
Integration and deployment
We deploy across cloud, on-premises and hybrid infrastructure, with API compatibility, security and scalability.
- 08
Ongoing support
Continuous monitoring, fine-tuning and support keep the model performing after launch.
Technologies we work with
- Python
- TensorFlow
- Scikit-learn
- Pandas
- Jupyter
- Databricks
- Kubernetes
- AWS
- Azure
- Oracle
- Grafana
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
Professional Services · Generative AI, NLP
Custom LLM chatbot with document references for a consulting firm
In-house LLMno 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.
Read the case study
Medical image translation between tissue stains for a pharma company
Reused one 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.
Semantic company search for private equity deal sourcing
1 week of 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.
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
“AI Superior responded to all of our needs very carefully and considered them in the project.”
Built AI models and a dashboard for a pilot program that detects waste in drone imagery.
“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.
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
Industries that benefit from a custom LLM
We design each model for the challenges and demands of its sector.
Finance
Custom models for risk, analysis and reporting.
- Fraud detection
- Market analysis
- Automated financial reporting
Healthcare
Language models for clinical documentation and support.
- Medical transcription
- Diagnosis assistance
- Clinical documentation
E-commerce
Models that personalise and automate the customer journey.
- Recommendation engines
- Automated customer support
- Product description generation
Legal
Models optimised for legal language and regulation.
- Contract analysis
- Legal research
- Compliance monitoring
Marketing and content creation
Models that produce and personalise content at scale.
- Content generation
- Personalised advertising
- Social media automation
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
When is a custom LLM worth it?
When you need domain-specific accuracy, better performance on your own tasks or full control over your data. A custom model is designed for your industry applications rather than for general use.
Do you build on existing foundation models?
We can. Depending on your requirements we develop a proprietary model or build on top of a foundation model such as GPT, then train and fine-tune it for your use case.
Can the model be tailored to our business?
Yes. We train and fine-tune it with your own datasets and optimisation techniques, and can add multilingual support for real-time translation and localisation.
How secure is a custom-built LLM?
We follow privacy-first principles, with encryption, access control and compliance with your industry’s regulations built in from the start.
Where can the model run?
In the cloud, on your own premises or in a hybrid infrastructure. We ensure API compatibility with your systems, security and room to scale.
What does developing a custom LLM cost?
It depends on model complexity, the training data and your deployment needs. We scope the project with you and give you an estimate based on your requirements.
How do we get started?
Contact us to discuss your needs. We design a tailored strategy for developing and deploying your custom LLM.
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.