To the builders of the agentic future,
AI agents have a reliability crisis. After years of pilots, most enterprises still haven’t moved beyond chatbots and copilots. 2025 became the year everyone talked about agents, yet too few shipped autonomous workflows that survive production realities, policy constraints, and ROI scrutiny.
We believe autonomous agents will transform economies, just as autonomy already has in domains like self-driving. We live in a world where capable agents are possible but limited by us: by how we train them, how we evaluate them, and whether we give them a safe place to practice, fail, learn, and earn trust before they matter.The blockers are brittle systems and missing infrastructure. Unreliable agents mean ROI isn’t realized, investment slows, and progress stalls. Compliance and reliability remain unsolved in tandem. LLMs don’t work out of the box for regulated, tool-rich workflows. Integration and customization at the enterprise edge, e.g. email, Slack, ERP/CRM, card and payment APIs, policies, and humans, are hard, especially under load and in messy edge cases.
Veris is changing that. We provide a simulation-first training ground where enterprise agents can be safely exercised, graded, and improved before and after they touch production. Our sandboxes mirror the real world with mocked tools, realistic policies, latencies, and failure modes. Scenarios and personas evolve over time, confronting agents with ambiguity, edge cases, and adversarial pressure. Evaluation and governance are continuous, with scenario scores, reliability dashboards, policy-compliance metrics, and deployment gates tied to SLAs. The loop closes automatically: Veris generates data and labels from every run so agents can self-play, collect signals, and improve via SFT and RL. Everything is wrapped in enterprise rigor, i.e. audit trails, reproducibility, and change management, so updates ship with confidence.
Others offer pieces, Veris delivers the whole. The depth and breadth of our simulations across tools, policies, and adversarial conditions is unmatched. No one creates high-fidelity data and labels at this pace, then use them for continuous improvement. No one closes the loop so agents are trained, tested, certified, and steadily upgraded.
Our mission is to provide the definitive, simulation-first training ground where enterprise AI agents are rigorously tested, improved, and certified so organizations can deploy with reliability, compliance, and confidence. Our vision is an agentic future where software acts safely and autonomously, replacing fragmented SaaS workflows with trustworthy agents that deliver compounding ROI.
If you’re serious about agents, give them a place to grow up. See Veris in action with a focused walkthrough of our dynamic benchmarks. Drop your agent into a starter sandbox and watch it tackle real scenarios, good, bad, and adversarial, while you review policy checks, audit trails, and deployment gates mapped to your requirements. Request a demo to run your first scenario set and measure the lift.
Signed,
Mehdi Jamei, Co-Founder
Andi Partovi, Co-Founder
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