Agent Knowledge Layer
AI is only as good as what it knows about your business.
Without your context, a model guesses. We build the knowledge and retrieval layer that gives AI your documents, your data, and your terminology, with permissions and citations intact.
Part of
02Engineer
Turn possibility into production.
Data & knowledge engineering
Where this sits in the lifecycle
The problem
Ungrounded AI invents policy numbers and product names and states them confidently. The fix usually isn’t a bigger model. It’s better retrieval.
- Confident answers that turn out to be wrong
- Institutional knowledge trapped in PDFs, wikis, and people
- Search that matches words but misses meaning
- No control over what AI is allowed to read
How we work
Four steps. One team the whole way.
- 01
Audit the knowledge
Map the documents, databases, and systems that hold what the AI needs to know, and what it should never see.
- 02
Design retrieval
Chunking, embeddings, hybrid search, and reranking tuned to how your people actually ask.
- 03
Ground the answers
Responses built from your verified sources, with citations back to them.
- 04
Govern the lifecycle
Versioning, access control, and freshness rules, so knowledge stays accurate as it grows.
What’s included
What agent knowledge layer covers. In practice.
Semantic search & retrieval
Search that understands meaning and context, not just keywords.
Retrieval architecture
Storage and indexes designed for your data volume, query patterns, and latency.
Grounded generation
Answers drawn from your proprietary data instead of a model’s training data.
Data fusion
Documents, databases, APIs, and knowledge bases unified into one layer AI can query.
Knowledge governance
Versioning, access control, and freshness policies that keep it accurate and compliant.
Domain tuning
Retrieval tuned to your vocabulary, because “discharge” means one thing in healthcare and another in finance.
What you can hold us to
Commitments. Not marketing ranges.
What the knowledge layer commits to; accuracy is measured on your own questions during the build.
- answers
- Cited
- answers
- Responses link back to the source they came from
- aware
- Permission
- aware
- People only retrieve what they’re already allowed to see
- for all your AI
- 1 layer
- for all your AI
- Documents, databases, and APIs behind one queryable layer
Go deeper
More under Engineer, and beyond.
- EngineerTurn possibility into production. Build the applications, agents, integrations, and data infrastructure that put AI inside real business workflows.
- Agent EngineeringAgents that do the work inside your systems, not beside them.
- AI-Enabled Custom DevelopmentCustom software, built faster, and billed that way.
- Agent StrategyKnow which workflows AI should take on first, before you fund the build.
- Forward-deployed engineersHowever you start, our engineers embed with your team: your Slack, your repo, your standups.
Bring us your document sprawl. We’ll make it answerable.
Policies in one system, contracts in another, the rest in people’s heads. Tell us where it lives and we’ll show you what it takes for AI to answer from it, with citations.