Pennsylvania · Applied AI
Semantic search (RAG) in Philadelphia
Built and supported here – the way a Philadelphia business would actually use it.
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.
Most of our Philadelphia engagements start the same way: a 20-minute call where the owner describes a workflow we've heard before in shape but never in detail. Semantic search (RAG) is then designed against the detail, not the shape.
- 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 Philadelphia businesses choose this
Philadelphia runs on healthcare, education and a manufacturing base that never fully left – AI here means modernising operations built up over decades, not starting from a blank slate.
Why Philadelphia businesses are a fit for this.
One of the largest hospital and university networks on the East Coast, alongside a manufacturing and logistics base with real history. Philadelphia businesses want AI that fits into how things already run, not a rip-and-replace.
We work with teams across Philadelphia: Center City · University City · Fishtown · Manayunk · Old City · South Philly.
How we build semantic search (RAG) for a Philadelphia team
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Philadelphia 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 Philadelphia teams
We'd call the engagement a success when Philadelphia 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 Philadelphia – common questions
What's a typical engagement length for Philadelphia businesses?
Six to twelve weeks for the build, then a short managed-services month while the system goes from "shipped" to "owned by your team". After that you keep us on retainer if you want, or take it from there yourself.
Are there hidden costs we should plan for?
Three to know about: model/API spend (which we set up under your own account, not ours, so you see and control it), any new SaaS subscriptions we recommend, and your team's time during rollout. We surface all three in the quote so there are no surprises.
What's the realistic outcome for Philadelphia 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.
Can you work with our existing systems?
Yes. The default semantic search (RAG) stack we reach for is Pinecone, Claude, Postgres pgvector, Vercel AI SDK, but we'll bend it around whatever you already run – Xero, HubSpot, Shopify, Cin7, your own in-house apps. The discovery week maps every data source before any build starts.
Skip the pitch.
Tell us the workflow and we'll come back with what we'd build first.
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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.