Dynamo AI

Dynamo AI is an enterprise platform for securing, evaluating, and governing generative and agentic AI systems. It helps teams add pre-production testing, runtime guardrails, and observability for compliance-focused deployments.

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Overview

Dynamo AI is an enterprise platform for securing, evaluating, and governing generative and agentic AI systems. The site describes it as a set of end-to-end controls for AI performance, security, and compliance, with products for pre-production testing, post-production guardrails, and agent security.

Its core purpose is to help teams identify risk before release, enforce policies at runtime, and monitor AI behavior in production. The product pages highlight use cases such as hallucination detection, jailbreak and prompt-injection defense, compliance guardrails, and continuous observability across AI workflows.

Core capabilities

Pre-production evaluation

Run automated AI evaluations and red-teaming to measure privacy, safety, and compliance risks before deployment.

Custom policy guardrails

Apply custom compliance guardrails that legal, risk, compliance, and cyber teams can tailor to specific requirements.

Hallucination detection and prevention

Detect hallucinations in real time and surface failure modes with root-cause analysis for problematic responses.

Unified observability

Log, audit, and monitor interactions across home-grown and third-party AI use cases from a single monitoring view.

AI-assisted policy writing

Use AI-assisted writing to draft policies with broader coverage and more detailed language.

Human review workflows

Review, adjust, and approve guardrail or evaluation results through human-in-the-loop workflows.

Practical use cases

Pre-launch AI evaluation
Use DynamoEval to assess security, privacy, safety, and regulatory risks before shipping a model or AI workflow into production.
Production guardrail enforcement
Use DynamoGuard to enforce guardrails on live generative AI applications, including hallucination checks, PII detection, and jailbreak filtering.
Agent and MCP security
Use AgentWarden to evaluate AI agents connected through MCP, identify risky tool combinations, and apply runtime policy decisions per tool call.
AI observability and audit trails
Use the observability layer to audit interactions across internal and third-party AI use cases and centralize monitoring for compliance review.
Policy authoring and review
Use AI-assisted policy writing and human review to translate governance requirements into operational rules and approve changes with traceability.

Pros and Cons

Pros

Covers the AI lifecycle with pre-production evaluation, runtime guardrails, and ongoing monitoring.
Supports custom compliance policies rather than only fixed, preset rules.
Includes specific controls for hallucinations, jailbreaks, prompt injection, and sensitive-data leakage.
Provides human-in-the-loop review for policy and evaluation workflows.
AgentWarden adds agent-specific security for MCP-based tools and enterprise connectors.

Cons

Public pricing is not available on the site pages provided, and the pricing URL currently resolves to a not-found page.
The provided pages do not include a full integration catalog or detailed setup requirements beyond AgentWarden’s client-hook and network-proxy options.

FAQ

Who is Dynamo AI for?

Dynamo AI positions the product for enterprise teams that need to productionize generative and agentic AI with guardrails, evaluation, and monitoring. The site highlights legal, risk, compliance, and cyber teams as stakeholders for custom compliance guardrails, and it also shows AgentWarden for securing AI agents and MCP-based workflows.

Is there public pricing information?

The public site does not show self-serve pricing or plan tiers. The pricing URL currently returns a not-found page, so pricing appears to require direct contact with the company.

How do the main products differ?

DynamoGuard is described as a post-production guardrail and observability product, while DynamoEval is positioned for pre-production AI testing and evaluation. AgentWarden focuses on agent and MCP security, including automated risk discovery, runtime policy enforcement, and continuous governance.

What integrations are documented?

The site describes integration via client hooks or network proxy for AgentWarden, including support for MCP clients, MCP servers, and network security providers. It does not publish a full integration directory on the pages provided.

What workflow does Dynamo AI support?

The site emphasizes real-time guardrails, hallucination checks, red-teaming, observability, and policy enforcement. It also states that human-in-the-loop review is available for guardrail and evaluation results.

Quick Facts

Category: Enterprise AI security and compliance
Primary products: DynamoEval, DynamoGuard, AgentWarden
Primary users: Enterprise AI, legal, risk, compliance, and cyber teams
Source domain: dynamo.ai
Deployment focus: Pre-production evaluation, runtime enforcement, and observability
Pricing: Not publicly listed on the provided pages