What it sells
Open-source agents to build predictive ML models from a prompt
Business model breakdown
Buyer: who owns the budget?
UnverifiedProduct, data and engineering leaders wanting AI in their product (inferred).
Trigger: what makes them buy now?
Most AI projects never reach production.
Workflow: what inputs become what output?
Embedded team (applied ML engineer, software engineer, engagement lead) builds on the Plexe backend for models and agents, deploys in customer VPC and hands over; customer owns IP.
Economics: what it saves and how it charges
Services-led applied AI lab plus platform; results claimed +7% conversion, -60% infrastructure cost, +20% enrollment, +28% repeat purchase.
Distribution: how it reaches customers
Sales-led: "Talk to us", "Speak to technical staff", cal.com booking.
Funding history and coverage
| Round date | Stage | Amount | Investors | Source |
|---|---|---|---|---|
| — | Y Combinator Spring 2025 | — | Y Combinator | ycombinator.com |
Profiles summarize public reporting and company websites. Business-model notes are MaxBC's reading of that material, not confirmed facts; unknowns are left blank rather than guessed. Updated 2026-10-12.