Central Region · Applied AI
Semantic search (RAG) in One-North
Semantic search (RAG) that lives in your stack, not on a vendor's roadmap. Shipped from Central Region.
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.
One-North sits in a regional context that genuinely changes the build. Connectivity assumptions, the rhythm of the working week, the proximity of your team to your customers – none of those are details our default semantic search (RAG) template would catch.
- 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 One-North businesses choose this
One-North is Singapore's dedicated biotech, media and tech research precinct – AI here is judged by researchers and engineers, not procurement teams.
Our field notes from One-North builds.
Biopolis, Fusionopolis and a dense cluster of biotech, media and deep-tech startups sit inside one of the most concentrated research precincts in Asia. Businesses here expect AI built with real technical rigor, since many of them build AI themselves.
We work with teams across One-North: Biopolis · Fusionopolis · Mediapolis · Ayer Rajah · Buona Vista.
How we build semantic search (RAG) for a One-North team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your One-North 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 One-North teams
If we build the right slice first, One-North 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 One-North – common questions
How fast could we have semantic search (RAG) in production?
Eight to ten weeks for most One-North businesses. Faster if your data is in good shape and slower if we're untangling a legacy integration first. We'll give you a realistic number on the scoping call rather than the optimistic one.
What does semantic search (RAG) cost for a One-North?
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.
Anyone else in this space using semantic search (RAG)?
Plenty. Average search time drops from 6 minutes to 12 seconds. The interesting question is rarely "does it work" – it's "is your team ready to use the output." That's what we'd scope on the call.
What if our One-North doesn't have any data ready?
Most don't. Getting the data into shape – ingestion, cleaning, the lightweight contracts you need before any model is useful – is part of the engagement. For semantic search (RAG) specifically, we typically run that work on Pinecone, Claude, Postgres pgvector, Vercel AI SDK and assume messy starting conditions from day one.
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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Tell us what you're trying to do and we'll reply with how we'd build it — no obligation.