New Territories · Applied AI
Semantic search (RAG) in Sha Tin
Semantic search (RAG) that lives in your stack, not on a vendor's roadmap. Shipped from New Territories.
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 reason we take on work in Sha Tin is that the businesses here tend to be sharper about what they want than the brief lets on. Semantic search (RAG) for a Sha Tin team almost always ends up looking different to semantic search (RAG) for a downtown Auckland one.
- 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 Sha Tin businesses choose this
Sha Tin anchors the New Territories' manufacturing, logistics and science park economy – AI here means industrial-scale operations work, not office admin.
Our field notes from Sha Tin builds.
Hong Kong Science Park and a broad manufacturing and logistics base serving cross-border trade with mainland China sit here. Businesses want AI that handles scheduling, compliance and cross-border logistics without becoming the bottleneck.
We work with teams across Sha Tin: Science Park · Tai Wai · Fo Tan · Ma On Shan.
How we build semantic search (RAG) for a Sha Tin team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Sha Tin 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 Sha Tin teams
We'd call the engagement a success when Sha Tin 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 Sha Tin – common questions
How fast could we have semantic search (RAG) in production?
Eight to ten weeks for most Sha Tin 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 Sha Tin?
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.
Has this actually shipped for a real Sha Tin?
Yes. Average search time drops from 6 minutes to 12 seconds. We'll share comparable engagements on the call.
What if our Sha Tin 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.
Sketch this with us.
We'll map your real workflow before quoting anything.
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.