The company remembers, even when nobody is looking.
Persistent AI memory across a company's full document corpus
Their employees kept asking the same questions of the same documents. We built a memory layer that indexes the corpus, answers in context with citations, and learns from every correction the team makes.
Onboarding took six weeks because tribal knowledge lived inside Slack threads, drives, and PDFs nobody read twice. Employees re-discovered the same answers daily. Senior staff burned hours each week answering questions a memory system should answer once. The company had bought a search tool. The search tool returned files, not answers.
We indexed the full corpus with Gemini embedding 2 and a layout aware preprocessor for the messier file types. Built a custom memory layer that returns answers with citations to the source document and the exact section. Wired it into the team's existing chat surface so adoption did not require a new tool. Every correction the team typed was written back to the memory as a fact with provenance. Staged rollout team by team, with a feedback loop to the operator who owned each domain.
Onboarding time cut roughly in half. Senior staff reclaimed three to four hours per week. The memory system now answers internal questions with citations to the original document and the version the answer came from, which made compliance happy on its own.