Automate repetitive tasks
Intelligent document processing and AI-driven workflow automation cut manual work, reduce costs and put resources where they matter.
AI software services · Discovery to scale
AI Software Development Services, proven as an MVP, then scaled
We build AI software for companies that want to automate processes, make better decisions and run leaner operations. Every project starts with a feasibility check and an MVP tested on real results, so you scale only what has proven its value.
- Feasibility assessed before development starts
- An MVP tested on real-world results
- Scaled and integrated into your processes
- 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 AI software does for your operations
Reduce risk
Predictive analytics, AI-assisted reporting and data visualisation turn large datasets into real-time insights, so decisions rest on evidence.
Make decisions easier
NLP, computer vision and machine learning models automate processes, improve user interactions and support better decisions.
What we deliver
Our AI software services
The software we deliver most often, and the engineering work that keeps it reliable in production.
- 01
AI-powered process automation
Automation tools that streamline business processes, optimise workflows and reduce manual tasks.
- 02
Custom machine learning models
Models designed and trained for specific applications, from fraud detection and risk assessment to demand forecasting and anomaly detection.
- 03
AI-driven data analytics
Analytics that combine data science and machine learning to give you actionable insights for decisions and strategic planning.
- 04
Chatbots and virtual assistants
Conversational assistants that improve customer interactions and automate support processes.
- 05
Image and video analysis
Computer vision for automated image recognition, facial analysis, object detection and defect detection.
- 06
Data engineering and preparation
We collect, clean and structure your data so models get high-quality inputs and produce reliable results.
- 07
Edge AI development
Models optimised for edge computing, making real-time decisions on devices with limited computing resources.
- 08
Integration and deployment
We integrate AI into your existing infrastructure with minimal disruption to business operations.
- 09
Model optimisation and maintenance
We monitor model performance and refine the models so they stay accurate and efficient over time.
- 10
AI governance and security
Governance frameworks for compliance, bias mitigation and ethics, and security frameworks that protect models and support data protection compliance.
Technologies we work with
- TensorFlow
- PyTorch
- Scikit-learn
- OpenAI models
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
Government · Computer Vision
Pothole detection and road damage assessment for a public body
Automatedpothole detection, severity scoring and mapping
A deep learning platform that detects and evaluates potholes and road damage on different types of roads with minimal human intervention, and maps them for maintenance teams.
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.
Telematics-based driver scoring for usage-based insurance
Per trip driving score and personal discount
A deep learning model that analyses telematic data from drivers’ phones to detect driving behaviour, score each trip and calculate personalised discounts and safe-driving recommendations.
Automated information extraction from invoices
25x faster invoice processing
A web service that extracts data from different types of invoices, automating data entry for a multinational equipment distributor and saving 850 man-hours per month.
Roof detection and segmentation for a solar energy company
Automated roof detection and roof plane segmentation
Deep learning models that detect residential roofs in satellite images, segment them into distinct planes and estimate the area and dimensions of each, so solar panel installations can be planned efficiently.
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%
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.
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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.
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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).
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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.
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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.
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Peter Luck, M.Sc. AI Consultant Master’s in Business Engineering and Computer Science; product and project manager for machine-learning products.
Client reviews
5.0 Rated 5.0 by the people we build for
18 verified reviews on Clutch
“AI Superior showed a strong commitment to delivering high-quality solutions to us.”
Improves and maintains the data infrastructure of a credit solutions company: data pipelines, ML models and custom reports.
“They are not only great theoretical experts, but also deliver with their awesome hands-on skills.”
“I would be more than happy to speak to anyone about how much of a rock star you guys are.”
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.
- 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
-
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
AI software across industries
Examples of the software we build for each sector.
Insurance
Better customer interactions, automated claims and sharper risk assessment.
- AI-assisted policy documents
- Automated claims processing with AI-driven reports
- Fraud detection
- Personalised policy recommendations
Finance
Automated customer service, faster insights and support for compliance.
- AI-generated financial reports
- Market trend analysis
- Fraud detection
- Personalised investment strategies
Pharmaceuticals
Support for drug discovery, research and patient care.
- Drug development simulations
- AI-generated clinical trial reports
- Personalised treatment recommendations
- Predictive analytics for healthcare trends
Construction
Models for planning, safety and project management.
- AI-generated project blueprints and models
- Automated site monitoring and analysis
- Risk assessment reports
- Material and labour forecasting
Real Estate
Streamlined property management, marketing and valuation.
- AI-generated property descriptions and listings
- Pricing prediction models
- Automated document processing
- Personalised property recommendations
Oil and Gas
Data synthesis and predictive analytics for exploration, production and maintenance.
- Geological reports
- Drone and satellite monitoring analysis
- Predictive maintenance insights
- Resource allocation strategies
Media
Generated content, automated media workflows and audience insights.
- AI-generated articles and news summaries
- Video and image enhancement
- Sentiment analysis for media trends
- Personalised content recommendations
Government
More efficiency, transparency and public engagement.
- Policy briefs and reports
- Intelligent document automation
- Public service chatbots
- Predictive analytics for governance decisions
Tech Start-ups
Faster content creation, product development and customer engagement.
- Product descriptions and marketing content
- Chatbots and customer support automation
- User behaviour analysis
- UI/UX design automation
Space
AI for space exploration, satellite monitoring and mission planning.
- Satellite imaging analysis
- Predictive mission diagnostics
- Anomaly detection in space systems
- Space research insights
NGOs and Non-profits
Automation for social impact, fundraising and policy research.
- Grant applications and reports
- Automated impact assessment reports
- Fundraising engagement strategies
- Data-driven policy recommendations
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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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 do AI software development services cover?
Designing, training and deploying AI-driven applications that automate processes, analyse data and improve efficiency. With us that includes data preparation, model development, integration into your systems and ongoing optimisation of the models.
How does a project with you run?
In five stages. Discovery defines goals and assesses feasibility. Initial setup gathers and pre-processes data and selects models and tools. We then build an MVP and refine it on feedback and real-world results. Once validated, we scale the software and integrate it into your processes, and we keep monitoring and fine-tuning it.
Why start with an MVP?
An MVP tests what the AI can actually do on your data and in your processes before you commit to full-scale rollout. You scale only what has proven its value, and the models are refined on real results rather than assumptions.
Which industries do you build AI software for?
Our engineers and data scientists have delivered AI software in healthcare, finance, retail and manufacturing, and the use cases above show how we apply it in insurance, real estate, pharmaceuticals, government and other sectors.
How long does AI software development take?
Timelines depend on complexity, data availability and how much customisation you need. Development typically takes from weeks to months; we estimate it once discovery is complete.
How do we get started?
Contact us to discuss your project. We start with discovery and then guide you through strategy, model selection and implementation for your business objectives.
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.
Prefer to pick a time yourself?
Schedule a call