LLM consulting · Advice to delivery

LLM Development and Consulting Services with a strategy you can execute

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.

  • A clear view of where LLMs fit your business
  • Model choice matched to your data and goals
  • Safeguards for bias, privacy and hallucination
  • 57% of our team hold a PhD
  • German company, working under the GDPR

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Trusted by enterprises, scale-ups and non-profits

  • Boehringer Ingelheim
  • HUK-Coburg
  • World Vision
  • Finiata
  • zeile sieben
  • TVARIT
  • Digit AI
  • Spryfox
  • Cycled
  • Firnas Aero
  • nomads
What you gain

What LLM consulting gives you

Good advice on language models is specific to your data, your customers and your risks.

Investment where it pays

A strategy built on your goals, data and infrastructure shows where language models create value and where they do not.

A model that sounds like you

Training on your industry data and customising language, tone and style keeps answers relevant and aligned with your company identity.

Output you can trust

Ethical safeguards address bias and misinformation and protect user privacy, transparency and data security.

What we deliver

How we advise and deliver

Consulting and engineering in one team, so the strategy we recommend is one we can build.

  1. 01

    Data and infrastructure assessment

    We review your data and evaluate your current infrastructure to see what an LLM solution can realistically build on.

  2. 02

    Stakeholder interviews

    We interview your teams to understand the business, its processes and where language tasks slow it down.

  3. 03

    LLM strategy

    We turn the findings into a strategy aligned with your business goals, from the first use case to wider adoption.

  4. 04

    Model selection or creation

    We decide with you whether an existing model fits or a model tailored to your needs is the better route.

  5. 05

    Customisation to your business

    We expose the model to industry-specific data and tailor its language, tone and style to your company.

  6. 06

    Responsible AI framework

    Representative, diverse training data, active bias removal, multidisciplinary review and continuous monitoring against ethical guidelines.

  7. 07

    Development and integration

    Our engineers design the architecture, build the model, integrate it into your workflows and test it on your use case.

  8. 08

    Maintenance

    Monitoring, optimisation and troubleshooting keep the model effective as your business and the technology change.

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 project
Case studies

Results we delivered for our clients

All case studies
Chatbot web application showing a conversation list, a question, the model answer and an expandable Sources panel
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, takes a different kind of team. This is what you get with us.

01

Scientists, not generalists

AI Superior was founded in 2019 by AI researchers with published papers and patents. That depth runs through the whole team.

  • PhD57%
  • MSc28%
  • BSc15%
Team by highest degree
02

Built to reach production

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.

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 together, not handed over between separate 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.

  • Dr. Sergey Sukhanov 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 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. 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. 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. Peter Luck, M.Sc. AI Consultant

    Master’s in Business Engineering and Computer Science; product and project manager for machine-learning products.

Client reviews

Rated 5.0 by the people we build for

5.0
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.

Darko Stefanovic CTO & Co-Founder, Qode Interactive Verified on Clutch · Belgrade, Serbia
★★★★★
“They are not only great theoretical experts, but also deliver with their awesome hands-on skills.”
Sven Bunge Managing Director, zeile sieben Client testimonial
★★★★★
“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.

Carolina Milberg CEO, Stiftung GOLDKIND gGmbH Verified on Clutch · Germany
How we work

A proven AI project life cycle

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.

  • 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.
Start with discovery
  1. 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
  2. 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
  3. 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
  4. 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

    Go / no-go decision
  5. Evaluation

    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

Use cases by industry

LLM strategies for your sector

The right use case depends on the language, documents and customers of your industry.

Marketing and advertising

Content that resonates with your audience and lifts engagement.

  • Campaign slogans
  • Persuasive marketing emails
  • Tailored messaging
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.

  • Go Global Awards Winner 2021, International Trade Council Go Global Awards Winner 2021 · International Trade Council
  • Best Data Science & AI Service Provider, Europe 2021, German Business Awards Best Data Science & AI Service Provider, Europe 2021 · German Business Awards
  • Top Artificial Intelligence Company 2023, Clutch Top Artificial Intelligence Company 2023 · Clutch
  • Top Machine Learning Company 2023, Clutch Top Machine Learning Company 2023 · Clutch
  • Clutch Champion Fall 2023, Clutch Clutch Champion Fall 2023 · Clutch
  • Clutch Global Fall 2023, Clutch Clutch Global Fall 2023 · Clutch
  • Top BI & Big Data Company Germany 2023, Clutch Top BI & Big Data Company Germany 2023 · Clutch
  • Top IT Services Company Germany 2023, Clutch Top IT Services Company Germany 2023 · Clutch
  • Top Artificial Intelligence Companies 2023, TrueFirms Top Artificial Intelligence Companies 2023 · TrueFirms
  • Top Machine Learning Companies 2021, Techreviewer Top Machine Learning Companies 2021 · Techreviewer
  • Most Reviewed IT Services Companies Germany, The Manifest Most Reviewed IT Services Companies Germany · The Manifest
FAQ

Frequently asked questions

Something else on your mind? Ask us directly.

Where can LLMs help our business most?

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.

How do you deal with hallucination?

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.

How do you make sure the model is unbiased?

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.

Can the model reflect our company’s voice?

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.

Can LLMs replace our content creators or service agents?

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.

Is training an LLM time-consuming?

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.

How do we get started?

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.

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:

  1. We review your request and reply by email.
  2. A call with an AI expert to understand your problem, data and goals.
  3. A clear recommendation: the approach we suggest and a high-level estimate.

Prefer to pick a time yourself?

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