Target by what they actually prescribe.
Part D prescribing patterns, Open Payments relationships, and specialty-aware scoring — so your field team calls the prescribers who matter for your molecule, prepared.
Target lists go stale
Deciles from last cycle, spreadsheets from the data team, and no way for a rep to ask a new question without a ticket.
Relationships are opaque
You can't see who is already deep in competitor speaker programs — or who is an active investigator in your therapeutic area.
Pre-call prep eats the day
Publications, trials, affiliations, recent news — assembled by hand for every priority HCP.
Open Payments, made searchable
Payment-level Sunshine Act data rolled up by manufacturer and payment type, with engagement flags for active speakers, consultants, and principal investigators — and it responds to plain English: "rheumatologists with heavy pharma speaker relationships."
Learn more →Describe the prescriber, get the list
Specialty, geography, prescribing behavior, and relationship signals resolved from one sentence — no taxonomy charts, no analyst queue.
Learn more →The dossier, before the call
Publications, trial involvement, conference appearances, and practice news — gathered, synthesized, and cited on demand for any HCP in your pipeline.
Learn more →A queue that learns your wins
Explainable 0–100 scoring across fit, readiness, and reachability — tuned by your recorded outcomes, not a generic model.
Learn more →Works inside your AI assistant
Connect Claude, ChatGPT, Cursor, or any MCP client and run the whole workflow — plain-English search, campaign scoring, cited research, exports — under per-user OAuth consent and org-level admin controls. Included on every paid plan and the free trial.
Learn more →Prescribing patterns by drug and drug class — the ground truth for pharma targeting.
Five years of payment-level industry relationships, by manufacturer and nature of payment.
Investigator activity and publication history for KOL and speaker identification.
Verified identity, specialty, licensure, and disciplinary history.
Let the agents
do the research.
Your team does
what it does best.
Want proof first? Read an example dossier — sample data, real mechanics.