Internal Knowledge Assistants

What this looks like in practice

A new hire opens a chat panel and types: “what’s the lead time on these stainless bearings from supplier X?” The assistant pulls the answer from your past purchase orders, vendor email threads, or a spec sheet that lives in a SharePoint folder. It returns the answer with a source link. If the answer is ambiguous, it says so and points to the two conflicting sources. The senior estimator stops being interrupted ten times a day.

Behind the scenes, we build a retrieval-augmented setup over your real source-of-truth documents: vendor spec PDFs, your catalog spreadsheet, prior project notes, internal SharePoint or Google Drive folders, the Slack channel where the dispatcher answers questions all day. We use vector search (typically Pinecone or pgvector) over your indexed documents, with a model (Claude or GPT) that drafts answers grounded in the retrieved sources. The interface lives wherever your team already works — Slack, Teams, or a simple internal web page.

What the team experiences differently: the questions that used to interrupt the most experienced person stop hitting their inbox. The new hire stops feeling like they have to choose between asking and figuring it out alone. The institutional knowledge that walked out the door when somebody retired stops walking out.

Where this fits best

Highest ROI in businesses where institutional knowledge is the bottleneck — distributors with deep technical catalogs, fab shops with vendor-specific quirks, field-service companies with site-history that lives in everyone’s head. If your training program is “follow the senior person around for six months,” this is the workflow that compounds the most.

What this isn’t

This is not a customer-facing chatbot. We do not deploy this to your public site or to your customer support inbox in v1 — the trust calibration is harder and the failure mode is worse. This is for your team. It is also not a search engine; it summarizes and answers, with sources, but does not replace browsing the underlying documents when the question is high-stakes.