Oregon · Applied AI
Semantic search (RAG) in Portland
Semantic search (RAG) that lives in your stack, not on a vendor's roadmap. Shipped from Oregon.
What semantic search (RAG) actually does
Search that understands intent, not just keywords. Your team types what they mean – and gets the right document, ticket, or product from across every system, with citations.
Portland sits in a regional context that genuinely changes the build. Connectivity assumptions, the rhythm of the working week, the proximity of your team to your customers – none of those are details our default semantic search (RAG) template would catch.
- 01 Indexes Drive, SharePoint, Notion, Slack, your CRM
- 02 Returns answers with source links – no hallucinations
- 03 Permissioned so staff only see what they should
- 04 Re-indexes nightly so results stay fresh
Built on: Pinecone Claude Postgres pgvector Vercel AI SDK
Why Portland businesses choose this
Portland runs on a mix of tech, manufacturing and a famously independent small business scene – AI here has to respect a market that's skeptical of hype by default.
What we keep seeing in Portland.
A semiconductor and tech manufacturing base (the 'Silicon Forest'), and a dense scene of independent retailers, restaurants and makers. Portland businesses want AI that's genuinely useful, not just the current trend.
We work with teams across Portland: Downtown Portland · Pearl District · Hawthorne · Beaverton · Hillsboro · Lloyd District.
How we build semantic search (RAG) for a Portland team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Portland 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.
AI search over your data.
The outcome for Portland teams
Average search time drops from 6 minutes to 12 seconds. For Portland teams, that almost always shows up as fewer interruptions and a calmer week, not a dashboard chart.
Average search time drops from 6 minutes to 12 seconds.
Semantic search (RAG) in Portland – common questions
What's the realistic timeline for semantic search (RAG) with a Portland?
Most Portland businesses have their first usable slice in week 5 or 6. We'd rather ship narrow and real than broad and aspirational – your team gets to use the thing well before the engagement is "done".
What does semantic search (RAG) cost for a Portland?
Pilots start from a fixed scope priced to land a measurable result inside 6 weeks. Pricing depends on data volume, integration complexity, and whether you need us on managed services afterwards. We'll quote precisely after a 30-minute scoping call.
Has this actually shipped for a real Portland?
Yes. Average search time drops from 6 minutes to 12 seconds. We'll share comparable engagements on the call.
What happens if we want to swap a vendor out later?
Semantic search (RAG) is built behind a small adapter layer specifically so swapping a model provider or a data source is a one-day job, not a re-architecture. Pinecone, Claude, Postgres pgvector, Vercel AI SDK are our defaults, but the build is intentionally portable.
One reply, one direction.
We don't run sequences or follow-up automation. One useful answer, one decision on your side.
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.