Bayes Predictive

AI feasibility + activation layer

From protocol to patient-ready sites in hours, not weeks.

Actionable insights for modern clinical programs. Empowering CROs, sites, and sponsors with AI-driven solutions designed to eliminate manual bottlenecks and accelerate clinical, medical, and commercial decision making.

900+

clinical-ready sites and PIs

80%

of feasibility work automated

Weeks → hours

site response turnaround

Built for both sides of the trial

One platform. Two perspectives.

Bayes Predictive is an activated site network — sponsors and CROs identify best-fit sites and push activation workflows; sites cut admin and win more studies.

01 — Sponsors

For Sponsors & CROs

Explore sponsor solutions
  • Rapid study budget estimates
  • Ranked site recommendations from a verified network
  • One-click activation
  • Continuous site intelligence

How it works

Accelerating the path from protocol to patient.

Three connected steps move a study from a protocol document to ranked, activation-ready sites — without the email chains.

  1. 01

    Ingest

    Upload or paste your protocol. AI extracts and structures the requirements — population, capabilities, geography, timeline.

  2. 02

    Match

    AI-enabled budgeting and matching against verified sites and PIs by therapeutic area, population, capabilities, and trial history.

  3. 03

    Activate

    Push-button NDA and FQ workflows to selected sites. Ranked, scored responses with readiness signals in one dashboard.

Proof

Proven at the edge of clinical operations.

Innovo Research — SMO, 26 sites

Situation · A manual feasibility system was consuming 20+ hours per week across repetitive entry, scattered documents, and email back-and-forth.

What we did · Bayes Predictive automated 80% of Innovo's feasibility process, freeing FTE for higher-value work.

turnaround time
2+ wks → 48 hrs
increase in studies closed
65%
decrease in admin time
90%

Cardiovascular diagnostic & device company

Situation · Original sponsor estimate was 6–12 months for patient enrollment. Bayes Predictive matched the study to high-performing sites with patients ready to enroll.

What we did · A multi-month enrollment program collapsed to weeks by bypassing traditional feasibility and site selection.

enrolled with 0 screen fails
50 patients
site selection cycle time
25 days
to complete enrollment
15 days

Ready when you are

Accelerate your next study with Bayes Predictive.

Tell us a little about the trial. We'll show you the network — and what activation looks like in days, not months.

Get in touch