Context Engineeringfor Enterprise AI
AI fails without context. We structure your organisational knowledge into machine-readable context layers so AI agents can reason, act, and operate across your entire business.
The context layer
We build the missing layer between your organisational knowledge and your AI models. Structured context that makes enterprise AI reliable, accurate, and operationally useful.
Context Engineering
We structure your organisational knowledge so AI models can reason with it. Scattered documents, Slack threads, and tribal knowledge become machine-readable context that agents consume reliably.
Company Knowledge Graphs
Strategic decisions, product architecture, research, and customer insights connected into a single traversable graph. AI agents navigate your entire organisation instead of searching one tool at a time.
AI Agent Infrastructure
Production-grade infrastructure for deploying context-aware AI agents into your existing tools and workflows. Agents that pull from structured context to reason, act, and operate autonomously.
Semantic Knowledge Layers
We build the semantic layer between your raw data and your AI models. Consistent definitions, relationships, and access patterns that ensure AI outputs are accurate and grounded in reality.
Enterprise AI Readiness
We audit your organisation's knowledge, map your data landscape, and identify the gaps preventing reliable AI adoption. Structure first, deploy second.
Context-Aware Automation
AI agents that understand your business context and execute work across departments. Not just task automation but intelligent operations powered by deep organisational understanding.
Context is the new codebase
The future of enterprise AI isn't building bespoke software from scratch. It's structuring your organisation's knowledge so AI models can pull and act on it instantly.
We help companies map their teams, projects, research, and operational knowledge into structured context layers that any AI model can consume. Scattered documents, Slack threads, and tribal knowledge become a queryable, agent-ready knowledge base.
The companies that win aren't the ones with the best models. They're the ones with the best context.
# Engineering Team ## Overview Core platform engineering responsible for agentic infrastructure, API orchestration, and production deployment pipelines. ## Active Agents - **CI/CD Pipeline Agent** — automated build, test, and deployment across 12 services - **Code Review Agent** — PR analysis with context-aware suggestions - **Incident Response Agent** — real-time alerting and root cause analysis ## Stack TypeScript · Python · Next.js · FastAPI Supabase · Vercel · AWS Lambda
Context systems we have deployed
Production-grade context infrastructure powering AI agents with structured organisational knowledge, company knowledge graphs, and semantic layers. Deployed and running 24/7.
Personal Health Data AI Platform
AI data orchestration platform that unifies health, performance, and wellness data from multiple sources. Custom dashboards, knowledge retrieval systems, and conversational AI interface for personalised health insights.
Agentive: Context-Driven AI Agent Platform
A platform where non-technical users build and deploy AI agents powered by structured organisational context. Agents pull from connected knowledge layers to orchestrate APIs, CRMs, and business logic for 75,000+ users globally.
ReadyRNs: Medical Knowledge Architecture
Clinical knowledge structured into domain-specific context layers. 20+ AI tools for NCLEX prep, diagnostic reasoning, and nursing competency powered by RAG pipelines and medical knowledge extraction.
AI HR Compliance: Multi-Agent Context System
Enterprise multi-agent system with live government legislation as a structured context source. Automated compliance workflows and role-based AI agents that pull from regulatory knowledge graphs across healthcare staff.