AI services
Practical AI for the way your company works.
We help companies put artificial intelligence to work — from the first use case to solutions running inside daily operations, built on your own data and systems.
What we do
Eight ways we bring AI into a business.
Each service can stand alone or form part of a larger programme. We start from the business problem, not from the technology.
Discuss an AI project- 01
AI Strategy & Readiness
We review your processes, data and systems, identify where AI will actually pay off, and turn that into a prioritised roadmap with realistic costs and risks.
- Use-case discovery and prioritisation
- Data and infrastructure readiness review
- Roadmap, budget and value estimate
- 02
AI Assistants & Knowledge Search
Assistants that answer questions from your own procedures, manuals, contracts and reports — with references to the source document, and access limited to what each employee is allowed to see.
- Internal knowledge assistants
- Search across technical documentation
- Customer and employee support chatbots
- 03
Document Processing Automation
We automate the reading, classification and data entry of invoices, contracts, certificates, reports and forms — in Azerbaijani, English and Russian — so staff check exceptions instead of retyping documents.
- Data extraction from scans and PDFs
- Classification, routing and validation
- Summaries and translation of long documents
- 04
Process Automation & AI Agents
AI agents that carry out multi-step routine work across your systems — preparing reports, handling requests, reconciling records — with approval steps wherever a person needs to decide.
- Workflow and back-office automation
- Automated reporting
- Human-approval checkpoints
- 05
Predictive Analytics & Forecasting
Models that use your historical and live data to warn about equipment failures early, forecast demand and stock, and show managers what is likely to happen — not only what already has.
- Predictive maintenance and equipment health
- Demand, stock and cost forecasting
- Operational dashboards and anomaly alerts
- 06
Computer Vision
Video and image analysis on existing cameras: detecting missing protective equipment and entry into restricted zones, spotting leaks, corrosion and defects, and supporting quality inspection.
- HSE and site safety monitoring
- Visual inspection and defect detection
- Drone and CCTV image analysis
- 07
Custom AI Development & Integration
When an off-the-shelf tool does not fit, we build the solution and connect it to the systems you already use — ERP, CRM, document management, SCADA and data historians — in the cloud or on your own servers.
- Custom models and applications
- Integration with business and field systems
- Cloud, private cloud or on-premise deployment
- 08
Training & Adoption
Tools only create value when people use them well. We train managers and staff, write clear rules for the safe use of AI at work, and stay involved after launch to monitor quality and improve results.
- Training for managers and teams
- Internal AI usage policy
- Post-launch monitoring and support
Where AI helps
Typical applications by area.
We know energy and industrial operations from the inside, and apply the same discipline to office and administrative work.
01
Oil, gas & energy
- Early warning of pump, compressor and rotating equipment failures from sensor data
- Production data analysis to find losses and optimise well and facility performance
- Camera-based monitoring of PPE use, restricted zones and leaks
- Instant search across drawings, procedures, permits and inspection reports
02
Industry & manufacturing
- Maintenance planned by equipment condition rather than by calendar
- Automated visual quality control on the production line
- Energy consumption analysis and anomaly detection
- Spare parts, stock and supply forecasting
03
Office & back-office
- Finance: invoice capture, matching and reconciliation
- Procurement: tender document analysis and supplier comparison
- HR: an assistant for employee questions, CV screening support
- Legal and contracts: clause search, summaries and deadline tracking
How an AI project runs
Start small, prove the value, then scale.
A pilot on real data comes before any large commitment, so every further step is based on a measured result.
- Step 01
Discover
We study the process and the data behind it, and agree on one concrete problem and how success will be measured.
- Step 02
Pilot
A small working solution on your real data proves the value — or shows early that the idea is not worth scaling.
- Step 03
Deploy
We integrate the solution with your systems, set up access and security, and train the people who will use it.
- Step 04
Improve
We monitor accuracy and usage, fix what underperforms and extend the solution to further processes.
Our principles
AI you can rely on.
In industry, a tool that is wrong with confidence is worse than no tool at all. These are the rules we build by.
Your data stays yours
Confidentiality is agreed before work starts. Where data must not leave the company, solutions run in a private cloud or on your own servers.
People stay in control
AI prepares, suggests and checks. Decisions that affect safety, money or people remain with a responsible person.
Measured by results
Every project has a measure agreed in advance — hours saved, errors reduced, downtime avoided — and we report against it.
No vendor lock-in
We choose the model and platform that fit the task and your budget, and design solutions so they can be changed later.
Questions
What companies ask first.
Where should a company start with AI?
With one process that is repetitive, time-consuming and already has data behind it. A small pilot on that process shows the value quickly and gives the team experience before larger investments.
Is our data safe?
Data handling is defined in the agreement before any work starts. Depending on sensitivity, solutions can run in the cloud, in a private cloud or fully inside your own infrastructure, with access rights matching your existing ones.
Do we need a lot of data or our own IT team?
Not necessarily. Assistants and document automation work with the documents you already have. Predictive models need history, and the readiness review shows whether yours is sufficient. We can handle the technical side and work with your IT team where there is one.
Does it work in Azerbaijani?
Yes. Assistants and document solutions are set up and tested for Azerbaijani, English and Russian, including documents that mix languages.
Work with ICOA
Have a process AI could improve?
Describe the task that takes your team the most time. We will tell you honestly whether AI is the right tool for it and what a first step would look like.