Washington · Applied AI
AI knowledge base in Seattle
AI knowledge base that lives in your stack, not on a vendor's roadmap. Shipped from Washington.
What AI knowledge base actually does
Your team's tribal knowledge, finally searchable. Upload your SOPs, training videos, past emails, and Slack threads – your team asks questions and gets answers with citations.
Seattle businesses don't need another generic AI pitch. AI knowledge base only earns its keep when it's built around the workflow you actually run on a wet Tuesday, and that's how we scope every engagement we take on in Washington.
- 01 Ingests PDFs, Word docs, videos, Slack, Notion, Drive
- 02 Answers with citations back to source documents
- 03 Permission-aware – staff only see what they should
- 04 Detects stale docs and prompts owners to update
Built on: Claude Pinecone Vercel AI SDK Postgres MCP
Why Seattle businesses choose this
Seattle runs on cloud computing, aerospace and coffee, home to the companies whose infrastructure half the internet's AI runs on – AI here means holding up to serious technical scrutiny.
What Seattle teams tell us when they get on a call.
Two of the world's largest cloud providers are headquartered here alongside a major aerospace manufacturing base. Seattle businesses, even small ones, tend to have someone on staff who can and will check your work.
We work with teams across Seattle: Downtown Seattle · Capitol Hill · Bellevue · Fremont · Ballard · Redmond.
How we build AI knowledge base for a Seattle team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Seattle business, so value lands before the build is finished. Every engagement starts with a short call and a paid discovery if the brief needs one.
Internal AI knowledge base.
The outcome for Seattle teams
What changes for Seattle teams after this lands: the work that used to need a person stays done, the work that needs a person gets done with their attention undivided. New staff get to productive 3x faster – less senior-team interruption.
New staff get to productive 3x faster – less senior-team interruption.
AI knowledge base in Seattle – common questions
How fast could we have AI knowledge base in production?
Eight to ten weeks for most Seattle businesses. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.
What's the smallest engagement you'd take on?
A two-week paid discovery for Seattle businesses that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.
Anyone else in this space using AI knowledge base?
Plenty. New staff get to productive 3x faster – less senior-team interruption. The interesting question is rarely "does it work" – it's "is your team ready to use the output." That's what we'd scope on the call.
What if our Seattle doesn't have any data ready?
Most don't. Getting the data into shape – ingestion, cleaning, the lightweight contracts you need before any model is useful – is part of the engagement. For AI knowledge base specifically, we typically run that work on Claude, Pinecone, Vercel AI SDK, Postgres, MCP and assume messy starting conditions from day one.
One short call.
Tell us what you're trying to fix. We'll come back inside a working day.
Get in touch
Talk to us about this
Tell us what you're trying to do and we'll reply with how we'd build it — no obligation.