Selected work

Outcomes you can measure.

A look at how we work — pairing frontier AI with deep domain judgment to move the numbers that matter.

11xfaster insight-to-action cycle

Global biopharma

A predictive launch engine for a first-in-class therapy

Challenge: A first-in-class launch faced uncertain access and a field team flying blind on targeting.
Approach: We built an AI commercialization engine that fused claims, RWE, and field signals into weekly, steerable recommendations.
Outcome: The team reallocated effort in near-real time and exceeded its first-year access and uptake targets.

70%reduction in evidence cycle time

Specialty pharmaceuticals

Challenge: Years of real-world data sat unused; payers wanted evidence the team couldn’t produce fast enough.
Approach: We stood up a governed RWE platform and a reusable evidence pipeline with regulator-ready documentation.
Outcome: Evidence packages that once took months now ship in weeks, strengthening access negotiations.

3xfaster enrollment recovery

Clinical-stage biotech

Challenge: A decentralized trial stalled amid fragmented vendors, sites, and data standards.
Approach: We orchestrated the ecosystem end-to-end — unifying data, vendor governance, and patient experience.
Outcome: Enrollment recovered and the program hit its next milestone on the revised timeline.

Illustrative, anonymized engagements representative of our work — shown for confidentiality, not as named clients.

Tell us the number you need to move. We’ll show you how we’d move it.