Kowloon · Applied AI
Semantic search (RAG) in Tsim Sha Tsui
AI search over your data – wired into a Tsim Sha Tsui 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.
The reason we take on work in Tsim Sha Tsui is that the businesses here tend to be sharper about what they want than the brief lets on. Semantic search (RAG) for a Tsim Sha Tsui 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 Tsim Sha Tsui businesses choose this
Tsim Sha Tsui runs on trade, tourism and retail as one of the busiest commercial and shopping districts in Asia – AI here means never missing an enquiry across a market that never really closes.
What we keep seeing in Tsim Sha Tsui.
A major trading and export hub alongside a retail and tourism economy serving visitors from across the region around the clock. Businesses here want AI that answers enquiries and processes orders in multiple languages without a 24-hour roster.
We work with teams across Tsim Sha Tsui: Harbour City · Kowloon Park · Jordan · Yau Ma Tei · Hung Hom.
How we build semantic search (RAG) for a Tsim Sha Tsui team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Tsim Sha Tsui 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 Tsim Sha Tsui teams
If we build the right slice first, Tsim Sha Tsui 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 Tsim Sha Tsui – common questions
How fast could we have semantic search (RAG) in production?
Eight to ten weeks for most Tsim Sha Tsui 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 Tsim Sha Tsui?
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.
What's the realistic outcome for Tsim Sha Tsui 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 if our Tsim Sha Tsui 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 short call.
Tell us what you're trying to fix. We'll come back inside a working day.
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.