North Carolina · Applied AI
Semantic search (RAG) in Charlotte
Semantic search (RAG) that lives in your stack, not on a vendor's roadmap. Shipped from North Carolina.
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 Charlotte is that the businesses here tend to be sharper about what they want than the brief lets on. Semantic search (RAG) for a Charlotte 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 Charlotte businesses choose this
Charlotte is the second-largest banking centre in the country after New York – AI here has to meet a financial services standard for accuracy and auditability.
What Charlotte teams tell us when they get on a call.
Major bank headquarters and a dense financial services and fintech sector, alongside a growing logistics and energy base. Charlotte businesses expect AI that can show its work, not just produce an answer.
We work with teams across Charlotte: Uptown Charlotte · South End · NoDa · Ballantyne · Concord · Huntersville.
How we build semantic search (RAG) for a Charlotte team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Charlotte 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 Charlotte teams
If we build the right slice first, Charlotte 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 Charlotte – common questions
How fast could we have semantic search (RAG) in production?
Eight to ten weeks for most Charlotte 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 Charlotte?
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 Charlotte 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.