Services
We embed with your team and build the system around what you actually do.
No login, no seat licence, no platform to adopt. An engagement is engineers inside your operation, shipping production systems in weeks and leaving you something your competitors cannot buy.
The four phases, and what each one leaves behind
01
Embed & Map
Two weeks inside your operation, not on a call about it. We sit with the people doing the work and write down what they actually do: which spreadsheet, which exception, which thing they know that is written nowhere. That document is the specification, and it is usually the first time the process exists on paper.
You get: A written process map, a ranked list of automation targets, and an honest note on which ones are not worth building.
02
Architect
We design the system around your data and your constraints. Model choice comes last, because it is the part most likely to change. Retrieval strategy, evaluation, guardrails, failure handling and where a human stays in the loop come first.
You get: A system architecture, the data contracts it depends on, and the evaluation set we will judge it against before anyone writes production code.
03
Build & Ship
Production-grade AI deployed in weeks. Real data, real users, real load. We ship a narrow slice end to end before broadening it, because a slice in production teaches more in a week than a prototype teaches in a quarter.
You get: A running system your team uses daily, with tests, monitoring and a rollback path.
04
Compound
Every correction your team makes is a rule the system keeps. That is the difference between software you bought and an asset that gets harder to copy each quarter.
You get: A measured improvement loop, and a system your competitors cannot buy because nobody sells it.
What we build
AI strategy and system design
Where AI belongs in your operation and, more usefully, where it does not. Delivered as an architecture and a build sequence, not a slide deck.
Retrieval and RAG systems
Hybrid retrieval, reranking, chunking strategy and evaluation pipelines over your own documents and data. The part that decides whether the answer is right.
Multi-agent orchestration
Specialised agents coordinating on a real workflow, with fallback handling and human escalation, rather than one prompt doing everything badly.
Integration with the systems you already run
ERPs, CRMs, dialers, warehouse systems, government registries. The integration is usually the project; the model is rarely the hard part.
Data analytics and forecasting
Demand forecasting, anomaly detection and revenue leakage analysis built on your operational data, feeding decisions rather than dashboards.
Team enablement
Your engineers work alongside ours. When we leave, the system is yours to run and extend, and we document it on that assumption.
Where this fits, and where it does not
We are not
- A SaaS platform you log into
- A ChatGPT wrapper or AI chatbot vendor
- A consulting firm that delivers slide decks
- A one-size-fits-all product for any industry
- A freight forwarder, insurer, or energy company
We are
- Your embedded AI engineering team
- Builders of proprietary, production-grade AI systems
- Engineers who ship working software in weeks
- Custom-built around your exact operations
- The team that turns AI into your competitive moat