FOR COMMERCIAL L&D LEADERS IN BIOPHARMA

The AI commercial learning partner built for biopharma. Not adapted for it.

Most platforms were built for enterprise sales and retrofitted for pharma. Proxa Labs was built for biopharma from day one: advisory methodology, AI literacy programming, and a closed-loop platform designed around the constraints you actually operate in: MLR review, launch timelines, federated commercial structures.

The Closed Loop · Intelligent Commercial Readiness
Proxa Labs closed-loop diagramFour-product oval cycle showing Forge building content, Cue delivering learning, Stage assessing readiness, and Trace verifying competency.Intelligent CommercialReadinesscontent publishedreadiness reachedcompetency demonstratedgap → rebuildForgeBuilds MLR-compliant contentCueDelivers adaptive learningStageAssesses in live HCP roleplayTraceVerifies behavioral competency
Forge is active
AI agents generate MLR-compliant content from your PI, CSRs, and brand assets, with every claim cited automatically.

Trusted across biopharma and health systems

AbbVieAllerganAmgenAstraZenecaBayerBiogenBMSGenentechGSKJanssenMerckNovartisNovo NordiskPfizerRocheSanofiTakedaTevaGileadMass GeneralPenn MedicineMD Anderson
80–95%
of pharma AI pilots never scale or deliver measurable value
Source: Saama / Forbes, 2025
11 mo
average ramp to full rep productivity in biopharma
Source: Salesforce State of Sales, 2024
84%
of pharma reps missed quota last year
Source: Salesforce State of Sales, 2024
25 yrs
practitioner experience behind the Proxa Labs methodology
Proxa Labs
New
AI Literacy Program — the prerequisite every AI deployment needs.
Build AI fluency across every role before tools go live. Teams that understand AI adopt it. Teams that don't, resist it.
Four Principles for Evaluating Any AI Partner

How do you know if AI is actually working in your organization?

Most biopharma L&D leaders can't answer that question with confidence because the data that matters isn't in the dashboard.

These four principles are how Proxa Labs diagnoses whether AI is actually delivering, and how our practitioners have built 25 years of award-winning work around them.

01 — Methodology
We diagnose before we prescribe.
Every engagement starts with the question your organization actually needs answered: what will determine whether any AI implementation succeeds or fails here? Most vendors skip this. We never do.
02 — Compliance
Their compliance story is a retrofit. Ours is not.
MLR review, GxP validation, and compressed launch windows are the operating conditions Proxa Labs was designed around from day one.
03 — Insider
We don't need you to explain pharma to us.
Proxa Labs' practitioners have operated inside the environments they now advise. The failure modes are already known. That's 25 years of practitioner experience, not a talking point.
04 — Experiment
You don't commit until you have evidence.
Proxa Labs' model inverts the typical vendor sequence. We run structured experiments to test fit in your environment before you stake your credibility on it.
The AI Platform

Four products. One closed loop.

Content published in Forge → delivered by Cue → assessed by Stage → verified in Trace. Every gap automatically restarts the loop.

Forge
Agentic content creation.
AI agents build MLR-compliant training from your PI, CSRs, and brand assets. Hours, not months.
Cue
AI-powered adaptive learning.
Personalized pathways that close knowledge gaps in real time, ensuring reps are field-ready.
Stage
AI roleplay + compliance guard.
Live HCP conversations with AI physician avatars. ComplianceGuard monitors every message in real time.
Trace
Demonstrated field readiness.
Certification earned through behavioral competency — not attendance. 10-year audit trail.
"

We had been trying to make AI work for 18 months. Two pilots, two postmortems, and a CCO who was starting to ask whether L&D could actually lead this. What Proxa Labs did differently was refuse to let us skip the hard part — defining what success actually looked like before we built anything. We walked into our budget review with evidence, not a pitch deck.

Sarah Chen
VP, Commercial Learning & Development
Mid-Size Oncology Biopharma · Series C
23%
improvement in manager-assessed call quality
0
MLR compliance flags across all sessions
3 wks
from pilot conclusion to CCO approval
6 mo
full AI roadmap funded and in execution
When to Call Us

Built for the commercial L&D leader who's done with pilots that go nowhere.

If any of these sound like your situation, you're in the right place.

You have an AI mandate with no clear path forward
Your CCO wants results. Your IT and compliance teams want governance. Your budget requires ROI. You're navigating all three without a methodology.
You've run a pilot that didn't scale
It worked in the demo. It looked good in the pilot report. And then it died at the governance gate or got quietly deprioritized.
You have a launch in 6–9 months and content isn't ready
The commercial team needs field-ready reps. The content pipeline is behind. MLR review adds 60 days on a good day.
You're evaluating AI vendors and can't tell who to trust
Every vendor says they're built for biopharma. Every demo looks polished. You've been burned before.
Your L&D team is measuring completion, not performance
You know the CCO scorecard tracks rep readiness, call quality, and launch execution speed — not module completion.
You're building AI capability from scratch
No existing platform. No governance framework. No internal AI literacy. You need a structured starting point.
For Every Stage of the Journey

From where you are to AI-ready.

Four-plus years of InsiteX enterprise learning infrastructure in biopharma. A closed-loop AI platform built on top of it. You decide when and how fast to move.

01
Start where you are
InsiteX LMS or traditional content. Proven, compliant, built for pharma.
02
Assess your AI readiness
Advisory team maps your constraints before recommending anything. No technology pitch.
03
Build AI literacy across your team
Equip every role — reps, managers, medical affairs — with the fluency to adopt AI tools effectively.
04
Experiment before committing
Structured pilots generate evidence in your environment before you scale.
05
Deploy with confidence
Forge, Cue, and Stage built to survive your governance environment.

The mandate is clear.
The path forward isn't always.

Proxa Labs works with commercial L&D leaders who have been told to deliver on AI but haven't found a partner who understands what that actually requires in a biopharma environment. Start with a conversation. We'll tell you what we'd look at first.