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Most AI agents never make it to production. They stall in security reviews, fail compliance checks, or get blocked by risk committees who can’t verify what the agent will actually do. The gap isn’t capability—it’s trust. Enterprises need evidence that an agent is reliable, secure, and safe before they’ll deploy it. Vijil closes that gap. We provide the infrastructure to measure trust in AI agents, test for it systematically, defend agents in production, and improve them continuously based on real-world behavior.

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Trust Score

At the center of Vijil is the Trust Score—a quantitative measure of an agent’s trustworthiness across three dimensions:

Reliability

Does the agent do what it’s designed to do, correctly and consistently under normal and noisy conditions?
  • Correctness
    Behaves as expected in ideal conditions
  • Consistency
    Behaves as expected across similar inputs
  • Robustness
    Behaves as expected under noisy conditions and perturbations

Security

Can the agent resist malicious attacks and protect sensitive data?
  • Confidentiality
    Protects sensitive data from unauthorized access
  • Integrity
    Prevents unauthorized modifications
  • Availability
    Resists denial of service attacks

Safety

Does the agent avoid harmful outputs and respect boundaries?
  • Containment
    Operates within defined constraints
  • Compliance
    Adheres to policies and regulations
  • Transparency
    Provides justifications for decisions
The Trust Score turns trust from a subjective judgment into something measurable—evidence you can show to security reviewers, compliance teams, and business stakeholders.

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Build, Ship, Run, Evolve

Vijil lifecycle: Build with Depot, Ship with Diamond, Run with Dome, Evolve with Darwin Vijil covers the full agent lifecycle with four integrated products:

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Build with Depot

Start with components that are already hardened for trust. Depot provides guardrail models tuned for agent safety, hardened LLMs optimized for specific tasks, and pre-validated building blocks that reduce months of security work to days.

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Ship with Diamond

Test your agents before you trust them. Diamond evaluates agent behavior against hundreds of scenarios—reliability under stress, resistance to prompt injection, compliance with safety policies. You get a Trust Score and detailed findings in minutes, not weeks.

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Run with Dome

Protect agents in production. Dome provides real-time guardrails that filter harmful inputs and outputs, detect anomalies, and enforce policies—all with latency measured in milliseconds. When something goes wrong, you know immediately.

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Evolve with Darwin (in development)

Improve agents continuously. Darwin learns from production telemetry—the edge cases, the failures, the drift—and uses reinforcement learning to make agents more resilient over time. Trust isn’t static; Darwin keeps it current.

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Next Steps

Understand the Trust Score

Deep dive into how trust is measured across reliability, safety, and security.

Get Started

Set up your account and run your first evaluation.
Last modified on March 19, 2026