PeriMind: AI Tool Governance and Control Plane
PeriMind is designed for enterprises that need to manage risks associated with AI-to-system connections. It helps organizations enforce security policies and maintain audit trails across AI agents and LLMs.
At a glance
- Category
- Software Development
- Best for
- Enterprise Companies, Software Companies, CISO and Security Operations teams, AI Platform owners
- Pricing
- Pricing was not clearly available from the provided evidence. Buyers should confirm current pricing on the vendor website.
- Key use cases
- Governing AI Tool Calls, Enforcing Agent Policies, Compliance Audit Support, Analyzing Agent Intent
- Integrations
- MCP servers, APIs, CLI tools
- Official website
- cinchy.com
PeriMind acts as a governance layer between AI interfaces—such as agents, copilots, and LLMs—and internal tool endpoints, including APIs, CLI tools, and MCP servers. It is designed to authenticate agent identities and authorize specific actions based on defined policies.
The software is intended for enterprise companies in sectors such as financial services, technology, and manufacturing. It supports a federated governance model, which allows policy control to be managed across three tiers: enterprise, domain, and team levels.
By capturing the reasoning chain and creating cryptographic audit trails, the tool helps organizations track why an AI agent took a specific action, which may support regulatory compliance and security forensics.
Buyers should confirm if their technical teams have the necessary expertise with OPA/Rego, as the tool utilizes this engine for fine-grained policy control.
Key Features
A central catalog of tool endpoints, including MCP servers, skills, APIs, and CLI tools, along with their capabilities and ownership.
Supports the creation of fine-grained policies in Rego to control which agents can call specific tools under defined conditions.
Provides hash-chained logs of tool calls to provide evidence for compliance and incident response.
Captures the AI's reasoning chain alongside each tool call to provide visibility into the decision-making process.
Assigns unique identities and scoped credentials to AI agents to replace the use of shared API keys.
Enforces per-agent and per-tool rate limits to prevent agents from overwhelming internal systems.
A three-tier model that balances central control at the enterprise level with autonomy at the domain and team levels.
Use Cases
Managing how AI agents and copilots interact with internal databases, APIs, and cloud infrastructure.
Setting boundaries on data access and actions, such as restricting DELETE operations in production databases.
Maintaining records of AI-system interactions to support regulatory requirements such as the EU AI Act or SOC 2.
Using reasoning capture to review the logic behind an autonomous agent's actions for forensic analysis.
Best For
Integrations
Pricing
Pricing was not clearly available from the provided evidence. Buyers should confirm current pricing on the vendor website.
FAQ
PeriMind acts as a control plane between AI interfaces (such as LLMs or agents) and enterprise tool endpoints to authenticate, authorize, and audit every interaction.
It is designed to work with any AI agent, copilot, or LLM, including those from OpenAI, Anthropic, and Google, as well as custom-built agents.
It uses an OPA/Rego Policy Engine and a three-tier federated hierarchy, which allows policies to be established at the enterprise, domain, and team levels.
Based on the provided evidence, the software is primarily designed for enterprise companies and software organizations with complex infrastructure.
Source category: Software Development
Source subcategory: AI Development Platform
Software Type:
How AI is used
PeriMind is an AI governance control plane for enterprises that manages tool calls between AI agents and internal systems. It supports a federated policy model and captures reasoning chains for auditability. Implementers should note that the tool requires technical expertise to manage.
Pros & Cons
- Supports various interfaces including ChatGPT, Claude, and Gemini
- Provides visibility into AI reasoning chains
- Uses a tiered governance model for both central control and team flexibility
- Includes tamper-proof logs for audit purposes
- Requires high technical expertise for implementation
- Pricing is not clearly available from the provided evidence
- Policy management requires specific knowledge of OPA/Rego
