Agent Strategy
You know AI agents are the move. You don't know which workflows to target first. We run sprints against your real data and tell you exactly where agents will deliver.
Read moreAgent Knowledge Layer
An agent is only as good as what it knows
Your agents are guessing because they don't have context. We build the knowledge and retrieval layer that gives them access to your docs, your data, and your terminology.
Trusted by teams building and running mission-critical platforms
Challenges
The challenge with the status quo
Without context, agents hallucinate. They make up policy numbers, invent product names, and give confidently wrong answers. The fix isn't a better model. It's better retrieval.
Agents confidently giving wrong answers
01Institutional knowledge trapped in PDFs and wikis
02Search that matches words but misses meaning
03No governance over what agents can access
04Approach
How we deliver in production
One senior squad across all four stages, so nothing is handed between a strategy team and a build team. This is how agent knowledge layer runs from first workshop to production.
01
Knowledge audit
Map your data sources, documents, and knowledge bases — figure out what your agents actually need to know.
02
Semantic architecture
Design vector databases, embedding pipelines, and retrieval systems tuned to your data and query patterns.
03
RAG implementation
Build retrieval-augmented generation that grounds agent responses in your verified data, not training data.
04
Governance & lifecycle
Versioning, access controls, and freshness policies — so agent knowledge stays accurate and compliant.
Outcomes
What you get
Retrieval figures from knowledge layers running in production.
With properly tuned RAG pipelines
< 3%
hallucination rate
Across millions of documents
Sub-sec
retrieval
Docs, databases, and APIs unified into one queryable system
1 layer
for all your AI
Capabilities
What we deliver
What agent knowledge layer covers in practice, and what you can hold us to.
01
Semantic Search & Retrieval
Search that understands meaning and context, not just keywords. The right information, every time.
02
Vector Database Architecture
Vector storage designed for your data scale, query patterns, and latency requirements.
03
Retrieval-Augmented Generation
Ground LLM responses in your proprietary data. Accurate, contextual answers instead of confident guesses.
04
Data Fusion
Unify documents, databases, APIs, and knowledge bases into a single semantic layer your AI can query.
05
Knowledge Governance
Versioning, access controls, and freshness policies. Your knowledge systems stay accurate and compliant as they grow.
06
Domain-Specific Embeddings
Embedding models tuned to your industry and terminology — because "discharge" means different things in healthcare and finance.
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Next steps
Every agent engagement connects. Here's where to go from here.
Start here
Bring us your document sprawl
Policies in one system, contracts in another, institutional knowledge in people’s heads. Tell us where it all lives and we will tell you what it takes to make an agent answer from it, with citations.