Optimised processes
Design software analyses many project alternatives, and inspection models cut the time and cost of checking sites.
Industries · Construction
Artificial Intelligence in Construction: safer sites, fewer costly errors
Construction companies use AI to plan building systems, monitor sites and track how workers, equipment and materials interact, with alerts for safety issues, construction errors or low productivity. AI will not replace the workforce, but it reduces expensive mistakes and makes construction operations more productive.
- Site inspections automated with drones
- Unsafe behaviour detected in site imagery
- Lower inspection costs and fewer errors
- 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 changes in construction
Where AI already pays off on construction projects and sites.
Better risk management
Image recognition evaluates photos and videos from sites, identifies incorrect or dangerous behaviour and informs safety training.
Leaner customer service
AI handles routine customer requests such as questions, duplicate invoices and complaints, reducing the cost of dedicated support teams.
What we deliver
AI solutions for construction companies
Use cases we implement today, plus the trends shaping AI in civil engineering.
- 01
Drone-based site inspection
Computer vision detects, classifies and measures construction debris in drone imagery and shows the results on a GIS dashboard with APIs for other systems.
- 02
Safety monitoring from images and video
Image recognition and classification that flags incorrect or dangerous behaviour on site and supports the design of safety courses.
- 03
Design and planning optimisation
Software that analyses a large number of project development alternatives and continuously improves planning.
- 04
Big data on the construction site
Collecting and analysing site and environmental data to optimise decisions such as where to place structures, faster than manual field analysis.
- 05
Smart building systems
Combining motion sensors, presence-aware temperature control and smart elevators into buildings that save energy, time and money.
- 06
Personalised customer service
Chatbots and automation that answer questions, generate duplicate invoices and handle complaints for construction companies with direct customer contact.
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
Construction · Computer Vision
Drone-based construction debris detection for a city municipality
40%lower average inspection costs
A drone-based application that detects and reports 25 types of construction debris, automating construction site inspections and saving 320 man-hours per month.
Read the case study
Drone-based litter detection and collection planning
25x faster litter detection, with overall costs halved
A computer vision system that detects litter in drone images across roughly one thousand square kilometres of coastline, with a GIS application for planning and tracking collection.
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.
Pothole detection and road damage assessment for a public body
Automated pothole 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.
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.
“They successfully fulfilled every component of the project and exceeded our expectations.”
Built an AI model that analyzes the roofs of residential and commercial properties, including data collection and labeling. All key deliverables were completed on time.
“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.
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
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
Can AI really reduce inspection costs on construction sites?
Yes. For a city municipality we built a drone-based system that detects 25 types of construction debris, such as bricks, cement blocks and sand heaps, and estimates their size. By the client’s estimates it saved 320 person-hours per month and reduced average inspection costs by 40%. It has since been adopted by multiple municipalities.
Will AI replace construction workers?
That is unlikely. AI changes business models, reduces expensive errors and makes operations more productive, but people remain responsible for the work on site. Robotics for tasks such as assembly is an emerging trend rather than today’s norm.
Can the results integrate with our existing systems?
Yes. In our construction debris project, detection results were available on a GIS dashboard and through APIs, so they could be integrated with practically any other system.
How do you use images and video for site safety?
Image recognition and classification models evaluate photos and videos collected on site and identify incorrect or dangerous behaviour. The findings help teams target safety training where it is needed.
How is an AI project in construction run?
We follow an AI project lifecycle adapted from software development standards that also accounts for the scientific challenges of machine learning. Each phase has its own goals and quality criteria that must be met before the next stage begins.
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.