platform
Ship trusted agents at scale
Scaling agentic AI for real business value faces a predicament: delay deployment for evidence that agents are resilient, or build agents quickly that are risky and unsafe in production.
Vijil resolves this trust gap at the heart of enterprise AI. Evaluate before deployment, protect in production, and adapt to real-world conditions.
Embed trust in the agentic lifecycle
Agentic AI requires a new approach to maintaining resilience and trust for how software acts.
Between developers building agents focused on velocity to the business owners using agents to drive business value, is a new architecture, a new set of risks, and an emerging lifecycle.
Runtime behavior is non-deterministic, attacks exploit model reasoning rather than code vulnerabilities, and the threat landscape evolves daily. Trusting agents to be resilient and safe can’t be a one-off guessing game.
Vijil provides the only complete platform purpose-built for AI agent resilience across the entire lifecycle: evaluation before deployment, protection during production, and continuous, adaptive improvement from real world conditions.
Platform Benefits
CHALLENGE
Convert probabilistic systems into reliable enterprise services
How Vijil Helps:
Vijil is the only complete system purpose-built for AI agent resilience across the entire lifecycle: evaluation, protection, and continuous improvement.
CHALLENGE
Traditional QA and application security tools don't work for agents, making trust reviews a lengthy, subjective and contentious process.
How Vijil Helps:
Vijil frees up developers to focus on feature development - not manual audits and reviews. Vijil’s custom evaluation shows exactly where an agent fails and what threshold it achieves—turning "is this safe?" into an answerable question with audit-ready documentation.
CHALLENGE
Policies exist — but enforcement often doesn’t.
How Vijil Helps:
Vijil translates governance requirements into evaluation policies for reliability, security and safety, and automatically generates policy-driven guardrails from evaluation output. Legal, risk and governance teams can use Vijil’s Trust Score for objective assessment, whether in terms of reliability, risk thresholds, and acceptable safety boundaries.
CHALLENGE
AI security is bolted on instead of embedded in the deployment pipeline.
How Vijil Helps:
Vijil automatically translates trustworthiness evaluation policies from evaluation into guardrails to defend agents. Security is part of the development process, with runtime protection operating to minimize failures the testing identified, contain security risks, and prevent compliance violations. Development, engineering and security can work in lockstep to improve agent resilience based on actionable guidance generated from production telemetry.
CHALLENGE
Need agents in production to drive business value, but can't afford the reliability, security, and compliance risks.
How Vijil Helps:
Vijil provides the evidence stakeholders need to understand safety, resilience, and compliance risks, compressing the time taken to move agents into production by 4x. When agents are in production, Vijil ensures they remain resilient and generate value by reducing the time from attack detection to deployed fix to 2-3 hours from 2-3 weeks.
MEASURABLE RESULTS
Reduction in time to trust
Faster time to market for mission critical agents
Remediation latency reduction for production failures
Harden your agents for the real world with Vijil
vijil diamond
VIJIL diamond
Evaluate Agents As Part of the Development Process
Stop scrambling to answer security questionnaires 6 months into deployment. Diamond catches trust issues during development—so you pass enterprise security reviews in weeks, not months.
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VIJIL Dome
Protect Agents in Production
Your agents passed pre-deployment testing. Now ensure they stay trustworthy in production under hostile conditions.
vijil Darwin
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VIJIL Darwin
Continuously Improve Agent Resilience
Most security tools test once and hope nothing breaks. Darwin continuously improves agents to make them more resilient—adapting to attacks observed in production data to strengthen defenses automatically with reinforcement learning.
Agents that learn from attacks and get stronger—not just verified once.
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Integration & Deployment
Architectures: Hosted with scoped retention or deploy inside your VPC with the same features.
Setup: Point to a staging endpoint, run the starter pack, generate the first policy, place checks at the boundary, then promote to production.
Requirements: HTTP endpoint, service account for tools if needed, outbound access for evaluation runs.
SDKs: Multi-language SDKs and a REST API for any stack.
