California · Applied AI
Semantic search (RAG) in San Diego
Built and supported here – the way a San Diego business would actually use it.
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.
The version of semantic search (RAG) that works for a San Diego business is rarely the version a national vendor would sell you. We build the one that fits how your team actually operates – usually with fewer parts than the off-the-shelf pitch.
- 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 San Diego businesses choose this
San Diego runs on biotech, defence and tourism, with a research base that rivals much bigger cities – AI here has to be precise enough for scientists and simple enough for a hospitality team.
Where San Diego operators actually lose hours.
A dense biotech and life sciences cluster around Torrey Pines, a major naval presence, and a tourism economy built on year-round weather. San Diego businesses span from lab-grade rigor to hospitality speed, often in the same block.
We work with teams across San Diego: Downtown · La Jolla · Mission Valley · North Park · Chula Vista · Carlsbad.
How we build semantic search (RAG) for a San Diego team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your San Diego 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 San Diego teams
We'd call the engagement a success when San Diego teams are using the system without thinking about us. Average search time drops from 6 minutes to 12 seconds.
Average search time drops from 6 minutes to 12 seconds.
Semantic search (RAG) in San Diego – common questions
What's a typical engagement length for San Diego businesses?
Six to twelve weeks for the build, then a short managed-services month while the system goes from "shipped" to "owned by your team". After that you keep us on retainer if you want, or take it from there yourself.
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.
Do you have proof this works for San Diego businesses?
Direct case study: Average search time drops from 6 minutes to 12 seconds. Happy to walk you through full numbers on a call.
Can you work with our existing systems?
Yes. The default semantic search (RAG) stack we reach for is Pinecone, Claude, Postgres pgvector, Vercel AI SDK, but we'll bend it around whatever you already run – Xero, HubSpot, Shopify, Cin7, your own in-house apps. The discovery week maps every data source before any build starts.
Skip the pitch.
Tell us the workflow and we'll come back with what we'd build first.
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.