Problems found faster
With so much drilling across an area, automated detection at scale spots defects quickly and learns from each one, so recurring issues are resolved faster.
Industries · Oil and gas
Artificial Intelligence in the Oil and Gas Industry from the well site to the back office
Oil and gas has always been an early adopter of computing, from reservoir modelling to 3D seismic models. AI is the next step. We build systems that detect defects across drilling sites, support maintenance of equipment and take manual data entry out of operations.
- Defect detection at scale with drones
- Maintenance support for drilling equipment
- Document processing without manual entry
- 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 oil and gas
Where AI supports operations across a large and distributed asset base.
Optimised production time
Models that learn a well site over time support maintenance planning and keep drilling machines active for longer.
Leaner back-office processes
Computer vision and NLP extract data from documents such as invoices, removing manual entry and the errors that come with it.
What we deliver
AI solutions for oil and gas companies
The most common AI use cases in the sector, and the expertise we apply to them.
- 01
Detection with drones
Computer vision on drone imagery detects defects and damage across drilling areas, registers each finding and speeds up the response when similar problems recur.
- 02
Maintenance support
Systems that learn from a well location over time to support problem solving with less reliance on engineers on site. This area is still at an early implementation stage, and we are clear about what it can do today.
- 03
Production time optimisation
Data-driven maintenance planning that keeps drilling machines running for longer between interventions.
- 04
Automated document processing
An OCR-based pipeline that enhances scans, classifies documents, identifies information blocks and delivers structured data to your ERP.
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
Oil and Gas · Computer Vision, NLP
Automated information extraction from invoices
25xfaster 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.
Read the case study
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.
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.
Object detection in hyperspectral satellite imagery
10 x 8 px smallest object size recognised
An environmental monitoring solution, developed as part of our social responsibility programme, that detects small objects in hyperspectral satellite imagery with very high accuracy.
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
Where does AI deliver value in oil and gas today?
In detection at scale, for example analysing drone imagery across drilling areas; in maintenance and production time optimisation for drilling equipment; and in back-office automation such as extracting data from invoices and other documents.
What results has document automation delivered?
For a large multinational equipment distributor in the sector we built a service that extracts data from different invoice types into their ERP. It increased processing speed by a factor of 25, halved the error rate and saved 850 person-hours per month.
Can AI maintain drilling equipment without engineers?
Not fully. AI can learn from a location over time and support engineers in solving problems, but implementation in this area is still at an early stage. We scope such projects carefully and test them before relying on them in production.
Do you have experience with drone-based detection?
Yes. We have built computer vision systems that detect and classify objects in drone imagery, such as construction debris and litter, with GIS dashboards and APIs for integration. The same approach applies to inspecting large industrial sites.
How do you run an AI project in this sector?
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.