G2

Giovanni D.

Director

Small-Business (50 or fewer emp.)

6/23/2026

"Averta Makes Runtime AI Agent Security and Tool Governance Simple"

5/5

What do you like best about Averta?

What I like best about Averta is that it has been built to solve a very specific challenge, securing AI agents at runtime, and it does this incredibly well. It tackles a problem that many enterprises either do not fully understand yet or have not been able to solve effectively.

It is not just another generic guardrail or monitoring layer. Averta gives teams a practical way to govern what agents can access, what tools they can use, and what actions they can take at runtime.

The UI and UX are clean and intuitive. It is clear that a lot of thought has gone into streamlining the experience, and the platform is easy to navigate day-to-day without feeling overcomplicated.

Integration has been very straightforward. Averta fits easily into the current architecture setup without needing a redesign, which is a major advantage. The MCP Gateway is especially valuable because it provides a governed way to connect agents to tools and integrations while controlling access and enforcing policy. There is already a strong range of integrations, and the team has communicated that this is actively being expanded.

Performance is another major strength. In normal workflows, you don't notice it running in the background, which is exactly what you want from a security layer. It performs well without disrupting existing agent workflows.

From an ROI perspective, the value is clear. Building this level of agent security, tool governance, and auditability internally would require significant engineering effort and would still be difficult to get right. Averta makes that capability available in a much more practical way.

The platform and documentation also make setup extremely easy, especially given how complex the problem is. Review collected by and hosted on G2.com.

What do you dislike about Averta?

The main area I would like to see expanded is the number of MCP connectors and integrations available out of the box. The current integration experience is strong, and the team has communicated that more connectors are being added, but a broader library would make adoption even easier across more enterprise environments.

One other area for refinement is the jailbreaking classification. It is effective, but it can sometimes feel a little restrictive depending on the use case. More tuning options or clearer ways to calibrate sensitivity by workflow would be helpful, especially for teams balancing strong protection with user experience. Review collected by and hosted on G2.com.

What problems is Averta solving and how is that benefiting you?

Before using Averta, securing AI agents at runtime was a difficult problem to manage. Basic LLM guardrails and traditional security tooling did not give enough control over what agents could access, which tools they could use, or what actions they could take once connected to real workflows.

We struggled with governing agent behavior across tools, APIs, MCP servers, and data access, but now we can enforce policies, control which tools agents can access through the MCP Gateway, detect risky prompts or jailbreak attempts, and maintain an audit trail from one dedicated platform. This has made it much easier to move AI agents toward production with confidence.

The biggest benefit is the reduction in internal engineering effort. Instead of spending significant time building and maintaining custom controls, Averta provides a purpose-built layer that fits into our existing architecture. That saves time, reduces security risk, and gives both engineering and security teams a clearer way to manage AI agent deployments. Review collected by and hosted on G2.com.