Startup packages · PoC, MVP, Product
Three fixed AI development plans cover each stage of a startup's product: a proof of concept, a minimum viable product and a full-scale product built on complex AI models. Each package has defined deliverables, a defined team and a predefined price, so you know what you get before work starts.
Start at the stage you are at. Each package ends with a result you can use and a roadmap for the next step.
Test the product concept and gain insight into customer needs: data analysis and quality report, preprocessing pipelines, a trained model, a demo or performance report and an MVP roadmap. Typically 3 to 6 weeks with a business analyst, a data scientist and an AI manager.
Validate the business model with an operational product (web, mobile or enterprise) with core functionality and an established framework for model training and deployment. Typically 4 to 8 weeks with two data scientists, a software engineer and an AI manager.
Scale from MVP to a full-scale product with complete functionality, automated data pipelines, documentation and knowledge transfer. From 10 weeks with a dedicated project team; scope and price depend on your requirements.
Concrete deliverables at each stage, so progress is measurable and nothing is left open to interpretation.
An extended analysis of your data set and a report on its quality and fitness for the use case (PoC).
Pipelines that prepare and extract the data your models need (PoC).
A working model trained on your data, shown in a real-time demo or a performance and usability report (PoC).
An MVP roadmap at the end of the PoC and a product roadmap at the end of the MVP, so each next step is planned.
A web, mobile or enterprise product with core functionality, ready for market validation (MVP).
An established machine learning framework for training and deploying your models (MVP).
An operational product with complete functionality and automated data pipelines (Product).
Documentation plus operational training and knowledge transfer sessions for your team (Product).
Not sure which of these you need? Describe the problem and we will recommend the approach.
Discuss your project
3,000man-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.
Read the case study
+5% diversity of content consumed by users
A personalised recommendation system that learns each user’s consumption patterns and preferences across diverse media content, helping a media company raise engagement, retention and customer lifetime value.
11.3% churn rate after new retention strategies
A machine learning model that learns player behaviour during the game and predicts the probability of churn over a given time horizon, so the platform can apply the most relevant retention strategy.
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.
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.
AI Superior was founded in 2019 by AI researchers with published papers and patents, and the whole team works to that research standard.
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.
Strategy, models and software are designed by one team, so nothing gets lost in hand-overs between 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. 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).
Dr. Sergey Sukhanov Advisor PhD in Machine Learning, data scientist since 2013. Publications, patents and 30+ implemented AI use cases; several IEEE awards.
“I would be more than happy to speak to anyone about how much of a rock star you guys are.”
“They are not only great theoretical experts, but also deliver with their awesome hands-on skills.”
“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.
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.
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
We review the results with you and make sure they are read correctly.
You get: What the solution delivered and where to improve next
Recognised by international business awards and by independent B2B platforms that rank companies on verified client reviews.
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 Each package has a fixed scope, defined deliverables, a defined team and a predefined price. You know the outcome and the budget before work starts, rather than working from an open-ended estimate.
If you still need to test whether AI can solve the problem with your data, start with the PoC. If feasibility is proven and you need to validate the business model, start with the MVP. If you have a validated MVP and need to scale, choose the Product package.
The PoC typically takes 3 to 6 weeks and the MVP 4 to 8 weeks. The Product package runs 10 weeks or longer, depending on scope and requirements.
The PoC team is a business analyst, a data scientist and an AI manager. The MVP team is two data scientists, a software engineer and an AI manager. The Product package has a dedicated project team.
Each package is offered at a predefined price agreed before work starts. The PoC and MVP have fixed price ranges; the Product package is priced on scope and requirements. Contact us for the current package prices.
Yes. We work closely with each client to understand their specific needs and tailor the plan to them, while keeping the scope and deliverables defined.
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