Vijil Raises $17 Million to Strengthen Trust and Resilience in Enterprise AI Agents

Vijil, a Menlo Park, California–based artificial intelligence infrastructure startup, has raised $17 million in a recent funding round, bringing its total capital raised to $23 million since the company was founded in 2023. The new funding is aimed at accelerating the adoption of Vijil’s platform, which is designed to help enterprises build, test, secure, and continuously improve the resilience of AI agents operating in production environments.

The company focuses on solving a growing challenge for enterprises adopting generative and agentic AI: trust. Vijil’s platform provides tooling that evaluates AI agents for reliability, security, and safety, while also enforcing governance controls and runtime protections. Its system uses production telemetry and reinforcement learning techniques to continuously improve agent performance and reduce the risk of failures or malicious exploitation. By addressing these issues, Vijil positions itself as core infrastructure for organizations moving AI agents from experimentation into mission-critical workflows.

The $17 million funding round was led by BrightMind Partners, a venture capital firm that invests in early-stage enterprise technology companies. BrightMind’s participation reflects confidence in Vijil’s approach to AI agent trust and security, particularly as enterprises increase reliance on autonomous systems. The round also included continued backing from Mayfield, through its AIStart seed fund, and Gradient Ventures, Alphabet’s AI-focused venture fund.

Mayfield and Gradient Ventures were also investors in Vijil’s earlier $6 million seed round, which the company raised in 2024 when it emerged from stealth. That initial funding supported the development of Vijil’s core products, including its evaluation framework and runtime defense services for AI agents. The continued participation of these investors in the latest round signals long-term conviction in Vijil’s product vision and execution.

Vijil was founded by former Amazon Web Services leaders with experience building large-scale cloud and AI infrastructure. The founding team’s background has influenced the company’s focus on enterprise-grade reliability, security, and scalability. Rather than offering a standalone monitoring tool, Vijil positions its platform as an integrated system that spans development, deployment, and ongoing operations of AI agents.

Early enterprise users have highlighted the operational impact of Vijil’s technology. According to the company, customers have used the platform to significantly reduce the time required to move AI agents from prototype to production, cutting deployment cycles from months to weeks. This speed-to-production advantage is becoming increasingly important as companies race to operationalize generative AI across business functions such as customer support, recruiting, and internal knowledge management.

The funding comes amid rising enterprise concern around AI governance and risk. As organizations deploy AI agents that can take autonomous actions, the potential for errors, hallucinations, and security vulnerabilities increases. Vijil’s platform addresses these risks by enabling continuous testing, policy enforcement, and adaptive hardening of AI agents in real-world conditions. This approach aligns with growing regulatory and internal compliance pressures facing large enterprises.

Vijil has also gained recognition from industry analysts for its work in AI trust and security. The company was recently named a Gartner Cool Vendor in the area of agentic AI trust, risk, and security management, highlighting its differentiated approach to making AI agents more resilient over time.

With the new capital, Vijil plans to expand its engineering and research teams, enhance its platform capabilities, and scale deployments with enterprise customers. As adoption of AI agents accelerates, the company aims to become a foundational layer for organizations seeking to deploy autonomous AI systems safely and reliably.