Thirty years of
enterprise lessons.
One AI company.
Built by someone who
lived the problems
these products solve.
Pressatto-AI was founded in South Florida after more than 30 years building and deploying enterprise software across some of the most recognizable names in the industry — PeopleSoft, Oracle, SAP, and SuccessFactors. Over those three decades, the same dysfunctional patterns appeared in every organization: hiring driven by gut feel, coaching that happened once a quarter if at all, and evaluation that varied wildly depending on who happened to be in the room.
The problems weren't hard to diagnose. They were hard to fix because no tool existed that combined deep enterprise domain expertise with modern AI capabilities. Generic AI tools didn't understand what a great SE demo looked like. Off-the-shelf ATS systems had no ability to evaluate a candidate's response — they just stored it. Coaching platforms generated summaries. Nobody was building the explainable, structured, auditable evaluation layer that enterprise teams actually needed.
That gap became Pressatto-AI. The company was founded with a single conviction: AI evaluation should be explainable, structured, and defensible — not a black box that spits out a score and expects you to trust it. Every product decision flows from that conviction, and every architecture decision flows from 30 years of knowing exactly what enterprise buyers need before they'll trust an AI system with a hiring decision or a performance review.
Pressatto-AI is structured as a SaaS holding company — building, owning, and operating AI-native products across talent acquisition (Merit2Hire), sales and coaching performance (Active Eval), and bespoke enterprise AI development. The business is intentionally lean: a solopreneur model that prioritizes building production-grade software over building an org chart.
From enterprise veteran
to AI founder.
Company founded in South Florida. Initial focus on the recruiting market with the RIAS prototype — the precursor to Merit2Hire. Architecture designed from day one for multi-tenant enterprise deployment.
Async AI interview evaluation platform launched at merit2hire.com. Recruiter workflow: LinkedIn sourcing → async interview → AI evaluation → structured decision report.
Sales coaching and evaluation platform available at merit4all.com with a 5-credit free trial. Expanded segment coverage in progress, including academic oral exams.
First custom development engagement: enterprise website and internal operations portals. Proof that the Pressatto-AI stack delivers for bespoke enterprise clients, not just product users.
Merit2Hire ATS integration, Google ADK multi-agent evaluation pipeline upgrade, and full Active Eval relaunch — in active development.
How we operate.
We build AI that solves real, measurable problems — not technology demonstrations. Every product decision is evaluated against one question: does this improve a decision someone actually has to make?
Multi-tenant isolation, RBAC, and audit trails are non-negotiable baselines — not optional add-ons. Enterprise buyers need to trust the infrastructure they're putting candidates and employees through.
Every product is tied to measurable outcomes: faster hiring signal, lower ramp time, defensible grades. If we can't measure the improvement, we haven't solved the problem.
Humans first.
In that order.
AI exists to sharpen human judgment, never to replace it. When interests conflict, we decide in this order:
- 1The people our AI evaluates
Fair, explainable, contestable decisions — for candidates, sales reps, and anyone our software scores.
- 2Our customers
Signal they can trust and defend.
- 3Our people
Employees and partners who build with us.
- 4Our vendors
Treated as we ask to be treated.
- 5Our shareholders
Rewarded by doing the above well — never instead of it.
Constraints, not features.
Every output carries its reasoning. If we can't explain it, we don't ship it.
Our AI surfaces signal earlier; people decide. Human-in-the-loop is an architectural constraint, not a feature.
Any decision our software touches can be reconstructed, traced, and defended — to a customer, a candidate, or a regulator.
See signal earlier — and be able to prove why.