California · Applied AI
Semantic search (RAG) in Oakland
AI search over your data – wired into a Oakland workflow, not bolted on the side.
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.
Oakland businesses don't need another generic AI pitch. Semantic search (RAG) 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 California.
- 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 Oakland businesses choose this
Oakland runs on logistics, healthcare and a wave of businesses priced out of San Francisco – AI here means Bay Area capability without Bay Area rent.
The pattern across Oakland engagements we've shipped.
One of the busiest container ports on the West Coast, a major hospital network, and a growing tech and creative scene that moved across the bay for the rent. Oakland businesses want the same AI rigor as San Francisco without the San Francisco price tag.
We work with teams across Oakland: Downtown Oakland · Jack London Square · Temescal · Fruitvale · Rockridge · West Oakland.
How we build semantic search (RAG) for a Oakland team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Oakland 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 Oakland teams
What changes for Oakland 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. Average search time drops from 6 minutes to 12 seconds.
Average search time drops from 6 minutes to 12 seconds.
Semantic search (RAG) in Oakland – common questions
What's the realistic timeline for semantic search (RAG) with a Oakland?
Most Oakland 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 Oakland?
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.
Can you walk us through a comparable build?
Yes – on the first call we'll pick the closest engagement we've shipped to what you're describing and walk through the outcome, the headcount and the time it took. Average search time drops from 6 minutes to 12 seconds.
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 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.