Solutions

Same engine. Four decisions it gets asked to make.

Every one of them runs the same four stages — find the market, enrich each target from its own published site, understand where it is exposed against competitors, score the list 0–100. RepVector selects datasets at runtime against your question, so it isn't limited to these four. They're simply the ones we've built out in depth.

Find → Enrich → Understand → Score

Four stages between your question and a call list you can defend.

01

Find

Ask in plain language. The AI reads the intent, resolves the place you named down to county and FIPS, and pulls the datasets that actually apply from the public catalog — no query syntax, no source picking. What comes back is the whole target universe for that market, not a sample.

02

Enrich

Each target is taken past the registry row. RepVector reads the organisation's own website for services, locations, phone numbers, and named decision-makers, and attaches the page every fact came from. If a fact isn't published, it says "not published" — it is never inferred.

03

Understand

Capabilities are lined up against competing providers to expose gaps and whitespace, and each target is re-read over time so you can see what changed — a new location, a new service line, a decision-maker who left — with the evidence URL beside it.

04

Score

Everything folds into one 0–100 fit score per name: published volume, payer mix, opportunity gap, web completeness, whether a named contact was found, and how recently the target changed. The breakdown is shown on the row, not hidden behind a black box.

Pharma market access, payers, staffing, private equity, and digital health run on the same catalog. If that's your team, run a query and see which sources come back.

What you get

What lands in the dashboard

One run produces the whole picture for a market — the names, the people at them, the gaps worth calling about, and the proof behind every figure.

A ranked call list with people on it

Organisation, address, phone, and — where the site publishes one — a named decision-maker with their title and the page it was read from.

Tiers with a stated reason per name

Tier 1, 2 and 3 targets, each carrying one line explaining why it ranked there and the source row that line came from.

A 0–100 fit score you can open

Volume, payer mix, opportunity gap, web completeness, named contact and change recency, each shown as its own contribution.

Charts that drill down

Volume, payer mix, capacity and population widgets — click any figure to see the rows, geography, vintage and query behind it.

A competitive matrix and a one-pager

Your targets against competing providers by capability, with whitespace highlighted, plus a cited one-page positioning summary as PDF.

A market plan, sequenced

A week-by-week territory plan built from the ranked list — who to see first, in what order, and the evidence behind the sequence.

Change alerts on the market

Saved markets are re-checked, so you get a digest of the providers, capabilities and locations that moved since your last run.

Exports that keep the receipts

CSV, Excel and a full PDF build report, each carrying query, parameters, geography, vintage, capture time and citation URL into whatever CRM you run.

Build the list for one county and see whether the names are right.

Ask in plain language. RepVector finds the universe, enriches each target from its own website, scores it 0–100, and hands you a ranked call list with phones, addresses and named contacts.

Build a target list free

3 free runs — no card required.