From analysis to execution.
Data, machine learning and generative AI for construction and industry.
Analysis
We assess your data landscape, business priorities, and operational constraints to identify where AI can create measurable value.
- Data opportunity assessment
- Clear goals and business impact
- Use case prioritisation
Machine Learning and Deep Learning
We train machine learning and deep learning models on your company's historical data and leave them working inside your tools, with a confidence margin on every prediction.
- Cost estimation and demand forecasting
- Training on real historical client data
- Launch and validation with real data
Generative AI and agents
We create AI systems that review market information and documents, and assistants that answer from your company's own knowledge.
- AI that reviews market information automatically
- Assistants that answer from your documentation
- Automatic analysis and reporting
What we actually build.
You hire one of the three services above. With them we build four kinds of systems, and we choose the technology for your case.
Predictive models
Demand forecasting, anomaly detection, cost estimation. Trained on your historical data.
Assistants over your documents
Q&A systems over your own documents, manuals, or knowledge base. Deployed with your data, not public.
AI hubs for enterprise
Modular platforms that group AI tools by department. Adding a new feature does not mean rebuilding anything.
Automatic analysis
Automatic systems to watch the market, review documents or follow your business.
Frequently asked questions
See all questionsWhat services do you offer?
We work in three service areas (Analysis, Machine Learning and Deep Learning, and Generative AI and agents) and use them to build four types of systems:
Predictive models: cost or demand estimation and forecasting from your data, with a confidence margin on every result.
Automatic analysis: AI systems that detect, analyse and score market information without manual work.
Assistants over your documentation: ask questions about your manuals and documents and get clear answers.
Custom AI platforms: department-based management applications that grow without being rebuilt.
What technologies do you use?
Predictive ML: scikit-learn, XGBoost, CatBoost, LightGBM and PyTorch.
Agentic pipelines: Claude and Gemini, with Python, Pydantic and OpenRouter.
RAG and chatbots: pgvector, hybrid search, Claude and OpenAI.
Platforms: React, Vite, FastAPI, PostgreSQL, Supabase, Docker and Electron.
Our API backends run on FastAPI and models are deployed on dedicated servers or within the client's environment.
How much does a project cost?
All projects are fixed-scope and bespoke — the cost depends on the scope, available data, and required level of integration. We don't publish standard pricing because we don't have off-the-shelf products. To receive a proposal, use our contact form.