Services
Data and applied AI engineering, one team end to end
We build all three layers: the data foundation, the intelligence and software on top, and the operations that keep it trustworthy. Engagements can start at any layer.
Technology we build with
Core practices
Where most engagements start and where our case studies go deepest.
- 01 Agentic AI Planner and worker agents with typed tools, bounded retries, cost ceilings and full tracing.
- 02 RAG and LLM systems Retrieval over private data, natural language to query and structured extraction, with citations and evaluation.
- 03 Data engineering Pipelines, lakehouses, vector and graph stores with contracts, quality gates, lineage and access control.
- 04 Machine learning and forecasting Forecasting, risk, churn, anomaly detection and recommendation models, shipped with monitoring.
- 05 Analytics and BI Dashboards and semantic layers in Power BI, Qlik, Tableau and Looker, with row-level security.
Supporting practices
Delivered alongside the core work, or on their own when that is what the problem needs.
- 01 AI for compliance Document review against regulation and your internal framework, gap scoring and drafted remediation with human sign-off.
- 02 DevOps, MLOps and LLMOps CI/CD, Kubernetes, observability, model deployment, LLM tracing and cost control for software, ML and LLM systems.
- 03 Custom software development Web and mobile apps, SaaS platforms, APIs and backends on Next.js, MERN, FastAPI and Flutter.
Embedded engineers
Our engineers working inside your team on monthly terms, onboarded within a week.
Starting point
The fixed-scope assessment that opens most engagements.
Technology
Chosen per engagement, not per preference
Where a client already has a platform, we build on it rather than around it. Model choice is an engineering decision: every system routes model calls through one gateway, so the model can change without the application changing.
AI, agents and LLMs
Retrieval and vector search
Machine learning
Data platform
Analytics and BI
Web, mobile and backend
DevOps, MLOps and LLMOps
Cloud
Start with a two to three week assessment
Send us the problem and the constraints. You get a written architecture, a risk register and a costed roadmap, and you keep them whatever you decide next.