Most vendors lead with a demo. We lead with a diagnosis.
Every Proxa Labs engagement starts with the question your organization actually needs answered: what will determine whether AI succeeds or fails here? Six diagnostic engagements, each time-bounded, each producing a deliverable you can act on. No open-ended retainers.
The thing that determines whether AI works is rarely the technology.
AI implementations in biopharma commercial learning fail in predictable ways. The use case is too broad. The pilot is scoped to succeed in controlled conditions that don't match the real environment. There's no path to a defensible business case. The governance gate kills the deployment after a successful technical demo. The business sponsor moves on. These failure patterns account for 80–95% of pharma AI pilot failures.
Proxa Labs' advisory engagements are designed around them. We diagnose where you are in the AI journey, where the specific risks live in your environment, and which engagement gives you the highest-leverage starting point. We don't recommend technology before we understand the constraints it has to operate in.
Every advisory engagement is time-bounded, produces a concrete deliverable — not a slide deck — and feeds directly into either a structured Lab experiment or a focused implementation workstream.
Pharma AI pilots fail because no one defines what success looks like before the pilot runs.
Pick the engagement that fits where you are.
Each is time-bounded with a concrete deliverable. None requires a long-term retainer.
The diagnostic call took 30 minutes and saved us 9 months of building the wrong thing. We had been about to issue an RFP for an AI roleplay vendor. The advisory team showed us our actual blocker was MLR throughput, not roleplay coverage. We funded a Forge pilot instead. Six months later we had measurable launch readiness gains and a CCO-approved AI roadmap.
Not sure where to start? That's the right conversation to have.
30 minutes. No demo. Tell us about your environment, what you've tried, and where you've been stuck. We'll tell you what we'd look at first.