Oregon · Applied AI
Semantic search (RAG) in Eugene
For Eugene operators who want a working pilot in weeks, not a year-long programme.
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.
We've worked with enough operators in Eugene to know that the brief that arrives in our inbox is rarely the brief that ends up shipped. The first thing we do on any semantic search (RAG) project is sit with your team for a day before we propose anything.
- 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 Eugene businesses choose this
Eugene runs on higher education, timber and a growing outdoor gear and sportswear industry – AI here means fitting a market that values craft over hype.
Why Eugene businesses are a fit for this.
A major public university, a timber and forest-products industry with deep roots, and a footwear and sportswear cluster that grew up around it. Eugene businesses want AI that's genuinely well-built, not just well-marketed.
We work with teams across Eugene: Downtown Eugene · Whiteaker · Springfield · South Eugene · River Road · Santa Clara.
How we build semantic search (RAG) for a Eugene team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Eugene 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 Eugene teams
If we build the right slice first, Eugene teams feel the difference inside the first month. Average search time drops from 6 minutes to 12 seconds.
Average search time drops from 6 minutes to 12 seconds.
Semantic search (RAG) in Eugene – common questions
When does semantic search (RAG) actually pay back?
Inside the first quarter, in our experience. We pick the first slice specifically because it's the highest-leverage workflow for a Eugene – so the savings start landing before the rest of the build is finished.
Do you do hourly billing or fixed price?
Fixed price for the pilot, every time. After that it's your call – fixed price per milestone or a small monthly retainer for ongoing iteration. We don't run open-ended T&M because it disincentivises us from finishing.
Has this actually shipped for a real Eugene?
Yes. Average search time drops from 6 minutes to 12 seconds. We'll share comparable engagements on the call.
Will this run on our own infrastructure?
Yes, where it makes sense. Semantic search (RAG) can sit entirely in your cloud account, with model calls routed through endpoints you control. We default to Pinecone, Claude, Postgres pgvector, Vercel AI SDK but the architecture supports your existing platform choices.
Skip the pitch.
Tell us the workflow and we'll come back with what we'd build first.
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Tell us what you're trying to do and we'll reply with how we'd build it — no obligation.