New York · Applied AI
Semantic search (RAG) in New York
AI search over your data – wired into a New York 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.
New York 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 New York.
- 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 New York businesses choose this
New York runs on finance, law, media and a professional services machine that bills by the hour – AI here earns its place by giving that time back, not by being impressive in a demo.
Our field notes from New York builds.
Wall Street firms, Big Law, and a media and advertising industry that never fully stops, all sitting on top of the highest labour costs in the country. New York teams want AI that survives contact with a real client deadline.
We work with teams across New York: Manhattan · Brooklyn · Queens · Midtown · Financial District · Long Island City.
How we build semantic search (RAG) for a New York team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your New York 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 New York teams
We'd call the engagement a success when New York 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 New York – common questions
What's the realistic timeline for semantic search (RAG) with a New York?
Most New York 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 New York?
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.
Has this actually shipped for a real New York?
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.
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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.