California · Applied AI
Semantic search (RAG) in Los Angeles
Semantic search (RAG) designed around the way a Los Angeles team actually runs.
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.
Los Angeles 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 Los Angeles businesses choose this
LA runs on entertainment, production and a sprawling small business economy across a huge metro area – AI here has to work for a one-location shop and a studio with the same reliability.
What Los Angeles teams tell us when they get on a call.
Film and TV production, a massive creative freelance economy, and small businesses spread across a metro area bigger than most countries. LA teams want AI that handles the admin so they can stay on the thing that actually makes money.
We work with teams across Los Angeles: Downtown LA · Hollywood · Santa Monica · Culver City · Burbank · Venice.
How we build semantic search (RAG) for a Los Angeles team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Los Angeles 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 Los Angeles teams
What changes for Los Angeles 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 Los Angeles – common questions
What's the realistic timeline for semantic search (RAG) with a Los Angeles?
Most Los Angeles 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".
Is semantic search (RAG) worth it for a smaller Los Angeles?
Often, yes – and counterintuitively the ROI is sometimes faster than for the big end of town because there's less integration overhead. We'll tell you honestly on the scoping call if it isn't.
What's the realistic outcome for Los Angeles businesses?
Average search time drops from 6 minutes to 12 seconds. We don't promise tenfold lifts because we don't see them outside of marketing decks.
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.
Twenty minutes, your call.
You describe what's broken. We'll tell you what we'd actually do about it.
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Tell us what you're trying to do and we'll reply with how we'd build it — no obligation.