Context Engineering
Your evidence, made answerable. Every answer cited.
What is Context Engineering?
Context Engineering is retrieval-augmented generation built on your own corpus: your documents ingested and made answerable, so an assistant drafts from your evidence and cites the source rather than improvising.
What problem does Context Engineering solve?
A general assistant answers from the open web and guesses. It cannot speak from your evidence, cite its sources, or be trusted with a board-level question. Meanwhile your real knowledge sits unread in PDFs and inboxes.
What’s included in Context Engineering?
Private corpus
Your documents ingested, chunked and embedded into a private retrieval store you control. Fast to query, and never handed to a public model for training.
Cited answers
Drafts, briefings and Q&A grounded in your record, every claim traceable to a document.
Decision framing
Scenario and option analysis for leadership: the evidence on each side, never a black box.
Governance layer
Access control, audit logging, citation enforcement. Humans approve; AI prepares.
How does Context Engineering work?
- 01
Your question and your documents become embeddings, matched on intent, not keywords.
- 02
The right passages are pulled from your governed evidence pool.
- 03
The model answers from that evidence. And cites it.
- 04
Update a source and the next answer reflects it, in minutes.
Institutional answers in seconds, grounded in your own evidence. Private by design.