Investment where it pays
A strategy built on your goals, data and infrastructure shows where language models create value and where they do not.
LLM consulting · Advice to delivery
Before you commit to a language model, you need to know where it fits, which model to use and whether your data and systems can support it. We assess your data, interview your teams and evaluate your infrastructure, then turn the findings into a strategy and help you build it.











Good advice on language models is specific to your data, your customers and your risks.
A strategy built on your goals, data and infrastructure shows where language models create value and where they do not.
Training on your industry data and customising language, tone and style keeps answers relevant and aligned with your company identity.
Ethical safeguards address bias and misinformation and protect user privacy, transparency and data security.
Consulting and engineering in one team, so the strategy we recommend is one we can build.
We review your data and evaluate your current infrastructure to see what an LLM solution can realistically build on.
We interview your teams to understand the business, its processes and where language tasks slow it down.
We turn the findings into a strategy aligned with your business goals, from the first use case to wider adoption.
We decide with you whether an existing model fits or a model tailored to your needs is the better route.
We expose the model to industry-specific data and tailor its language, tone and style to your company.
Representative, diverse training data, active bias removal, multidisciplinary review and continuous monitoring against ethical guidelines.
Our engineers design the architecture, build the model, integrate it into your workflows and test it on your use case.
Monitoring, optimisation and troubleshooting keep the model effective as your business and the technology change.
Not sure which of these you need? Describe the problem and we will recommend the approach.
Discuss your project
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
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.
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.
~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.
Lower churn most at-risk clients retained, per client feedback
An interactive tool that analyses social media data to reveal audience interests, social group affiliation and demographics, so a bank can target offers that build loyalty and reduce churn.
Many vendors can build a demo. Making AI work reliably on real data, inside real business processes, takes a different kind of team. This is what you get with us.
AI Superior was founded in 2019 by AI researchers with published papers and patents. That depth runs through the whole team.
Every project is de-risked in stages, with a go/no-go decision at each milestone, so budget goes only into solutions proven on your data.
Strategy, models and software are designed together, not handed over between separate vendors.
When data must not leave your organisation, we build on private, self-hosted models instead of third-party AI services.
Your project is led by senior data scientists and engineers with research backgrounds, supported by our product and development teams.
Dr. Sergey Sukhanov Chief Data Scientist PhD in Machine Learning, data scientist since 2013. Publications, patents and 30+ implemented AI use cases; several IEEE awards.
Dr. Ivan Tankoyeu Chief Data Officer PhD in Computer Science. Recognised by the IEEE GRSS Society, winner of the Global AI Hackathon 2017, Kaggle TOP500 data scientist (2014).
Sergio Frayle, M.Sc. Lead Data Scientist Master’s in AI, Pattern Recognition and Digital Imaging; 7+ years in image processing and computer vision, with publications.
Enrique Fernández, M.Sc. Senior ML Expert Master’s in Robotics and Mechatronics; builds and deploys complex AI solutions, particularly in computer vision and NLP.
Peter Luck, M.Sc. AI Consultant Master’s in Business Engineering and Computer Science; product and project manager for machine-learning products.
“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.”
“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.
Every stage ends with a result you can check. You never commit to the next stage before seeing the previous one work, so scope, budget and risk stay under your control.
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
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
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
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
Together we evaluate the results of the implementation and make sure they are interpreted correctly.
You get: A clear picture of the value delivered and where to improve next
The right use case depends on the language, documents and customers of your industry.
Content that resonates with your audience and lifts engagement.
Support for medical professionals in a complex environment.
A more customer-centric shopping experience.
Data-driven decisions and faster answers for customers.
Shorter response times and personalised, round-the-clock support.
Learning paths that adapt to individual strengths and weaknesses.
More time for high-value work through faster document handling.
Recognised by international business awards and by independent B2B platforms that rank companies on verified client reviews.
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 Typically in four areas: analysing market data and customer sentiment for better decisions, automating tasks such as summarisation and translation, personalising customer interactions around the clock, and producing content such as email and social media campaigns. The consulting phase identifies which of these matters most for you.
LLMs can produce misleading or false information, and this cannot be ruled out entirely. We reduce the risk by building with ethical considerations in mind from the start: guarding against bias and misinformation, respecting user privacy, keeping the system transparent and maintaining data security.
We curate representative and diverse training data, actively identify and remove biases, involve multidisciplinary teams and continuously monitor and refine the model against industry best practice and ethical guidelines.
Yes. Training on industry- and business-specific data teaches the model the context of your domain, and we customise its language, tone and style to match your company’s identity.
No. They automate tasks, generate drafts and assist customers, but they cannot replicate human creativity, empathy and judgement. The best results come from models that support your people on routine work while they handle complex cases.
Training is resource-intensive, and the time depends on hardware, data volume and model complexity. Part of our advice is choosing the approach, such as using or adapting an existing model, that meets your goals with a sensible investment.
Reach out via email or our contact form. We learn about your needs, guide you through the process and tailor the solution to your goals.
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