Asqav provides a dedicated compliance and accountability framework for developers who need to track and control the autonomous actions taken by AI agents. The platform acts as a gatekeeper that intercepts and validates agentic workflows in real-time. By integrating into common frameworks like LangChain or CrewAI, it captures every operation and subjects it to a series of checks. These scans look for sensitive data leaks, toxic language, or scope violations, allowing the system to automatically freeze an agent's activity if it strays from its defined boundaries. This transforms the unpredictable nature of AI agents into a controlled, observable environment. A notable technical detail is the use of RFC 3161 timestamps and Bitcoin anchoring, which provide a high level of proof that the logs haven't been altered after the fact. For businesses navigating the EU AI Act or other regional standards, the tool generates audit packs that map technical logs directly to regulatory requirements. This makes it more of a security-focused governance tool than a simple debugging dashboard, specifically designed for those who must prove their AI's behavior to auditors or legal teams.
Problem: Autonomous agents can sometimes deviate from their intended task or access unauthorized data.
Solution: Asqav acts as a policy gate that monitors agent actions in real-time and blocks any that violate predefined rules.
Example: An AI research agent attempts to access a restricted database, but the policy gate blocks the request and alerts the admin.
Problem: AI agents might inadvertently transmit personally identifiable information (PII) to third-party APIs.
Solution: The platform scans all agent payloads for PII or secrets and redacts them before the action is finalized.
Example: A customer service bot is prevented from sending a user's credit card number to a cloud processing service.
Problem: Regulated industries require proof of why an AI agent took a specific action.
Solution: Asqav creates cryptographically signed and timestamped audit logs for every operation the agent performs.
Example: During a financial audit, a company provides verifiable receipts showing the exact data used for an AI-driven trade decision.
Target audience: Best for: Enterprise AI developers, Compliance officers, Security engineers
Pricing: Open Source · Categories: Chatbot Development, Developer Tools, Law and legal
Tags: ai agent, API, developer tools, legal assistant, Reporting
Visit Asqav - The evidence layer for AI agents
Asqav is an open source compliance and governance platform that intercepts and validates the actions of autonomous AI agents in real time. It applies policy gates to stop unauthorized actions, redacts sensitive information, and generates cryptographically signed audit trails for regulatory compliance.
Asqav conducts pre-flight action verification, detects PII and exposed secrets, and stops agents that violate predefined operational rules. It integrates with LangChain and CrewAI, supports self-hosted payload signing, and uses RFC 3161 timestamping and Bitcoin anchoring to create tamper-proof logs and compliance audit packs.
Asqav is available as an open source tool. Developers and organizations can use its accountability and policy-checking features according to its open source license without paying licensing fees.
Asqav provides integrations for popular AI agent frameworks including LangChain and CrewAI, allowing developers to embed real-time validation and compliance logging directly into their existing agent workflows.
Asqav protects audit logs using cryptographic RFC 3161 timestamps and Bitcoin anchoring. This structure ensures that recorded agent interactions, payload scans, and execution histories cannot be altered or forged after they are logged.