Context Engineering
AI systems are only as useful as the context they can access. We structure your institutional knowledge into formats agents can reliably consume.
Most AI deployments underperform not because the model is wrong, but because the context is inadequate. We structure what your organization knows into formats AI can actually use.
Knowledge Architecture & Structuring
Processes, policies, decisions, and expertise mapped into structured, machine-readable formats — taxonomies and knowledge graphs that reflect how your organization actually works.
Prompt Engineering & System Design
The instruction layers, system prompts, and retrieval architectures that give AI agents reliable access to the right context. Prompt engineering is about the decision, not the phrasing.
Content Transformation for AI Consumption
Legacy documentation, SOPs, brand guidelines, and institutional memory converted into structured formats optimized for LLM retrieval.
RAG System Design
Retrieval systems that ground AI outputs in your authoritative, current organizational knowledge — not training data alone. Critical for healthcare and compliance-sensitive environments.
Context Quality & Governance
Version control, drift detection, and freshness monitoring to keep your context layer accurate over time. The same governance discipline as any other data system.
Agent Context Layers
Memory, tool access, and knowledge retrieval layers that give AI agents reliable situational awareness across workflows. The difference between useful once and useful every day.
EXPERTISE