Fact0

Fact0 is a tamper-evident audit layer designed specifically for AI agents operating in enterprise environments. It provides a cryptographically secure and immutable log of all actions, decisions, and context accessed by AI agents, enabling organizations to meet stringent security audit requirements. By integrating with existing agent frameworks, Fact0 captures detailed execution traces including inputs, outputs, tool calls, and internal reasoning chains, and seals them with hashing and digital signatures. This ensures that any attempt to alter or forge the audit trail is immediately detectable. The platform offers a centralized dashboard for security teams to review agent activities, verify log integrity, and generate compliance reports. Fact0 supports flexible deployment options, including on-premises and cloud, to align with enterprise data governance policies. At its core, Fact0 uses a combination of cryptographic techniques such as SHA-256 hashing, Merkle trees, and public-key infrastructure to create a verifiable chain of custody for every agent interaction. Each event recorded in the audit log is timestamped and linked to previous events, forming an append-only ledger that can be independently verified. This approach provides non-repudiation, ensuring that neither the agent nor the operator can deny actions that took place. Fact0 also integrates with enterprise identity and access management (IAM) systems to track which user or system initiated each agent task, adding an additional layer of accountability. Beyond logging, Fact0 includes policy enforcement features that allow security administrators to define rules about permitted agent behaviors. If an agent attempts an action outside predefined bounds, the system can block the action and flag it for review. This real-time policy engine helps prevent data exfiltration, unauthorized access, and other security breaches. The audit data can be exported to SIEM systems like Splunk or Elastic for correlation with ot

Category: AI Agent
Pricing: Unknown

Problem solved

Enterprises are rapidly adopting AI agents to automate complex tasks, but security teams often block their deployment due to concerns about auditability, data leakage, and unauthorized actions. Traditional logging mechanisms are insufficient because they can be tampered with and lack cryptographic verification of agent decisions. Fact0 solves this by adding a tamper-evident audit layer that records every agent action in an immutable, verifiable log. Security reviewers can independently validate that agents operated within policy after the fact, and real-time policy checks prevent violations before they occur. This reduces the time-to-approval for agent deployments and enables secure operation in regulated industries.

Use cases

A financial services firm uses Fact0 to log every trade order placed by an AI trading agent, providing immutable evidence for SEC audits.
A healthcare provider integrates Fact0 with an AI agent that processes patient records, ensuring HIPAA-compliant access logs and chain-of-custody.
An e-commerce company runs a customer support AI agent; Fact0 captures all conversations and actions to prove no personally identifiable information (PII) was mishandled.
A software engineering team deploys an AI agent that automatically submits pull requests; Fact0 creates a verifiable trail of all code changes for compliance reviews.
A procurement department uses an AI agent to negotiate with suppliers; Fact0 logs all offers and acceptances to create a non-repudiable audit for financial audits.
A government agency employs an AI agent to process FOIA requests; Fact0 ensures the decision process is transparent and auditable by oversight bodies.

Audience

Enterprise
Developers
ML Engineers
Data Scientists

Pros

Cryptographically tamper-evident logs ensure integrity and non-repudiation.
Seamless integration with popular AI agent frameworks like LangChain and AutoGPT.
Real-time policy enforcement prevents unauthorized actions before they occur.
Enterprise-grade deployment options (on-premises, cloud) with SIEM integration.
Comprehensive compliance reporting simplifies security reviews and audits.

Cons

Requires integration effort to instrument existing agents, which may involve code changes.
Potential performance overhead from real-time logging and cryptographic operations.
Dependence on a centralized audit layer might introduce a single point of failure if not architected with high availability.

Official website: https://fact0.io/

Canonical LambdaBase page: https://www.lambdabase.com/tools/fact0

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Fact0

Unknown

• Updated Sep 1, 2026, 10:12 PM

Fact0 is a tamper-evident audit layer designed specifically for AI agents operating in enterprise environments.

Use Cases ▼

A financial services firm uses Fact0 to log every trade order placed by an AI trading agent, providing immutable evidence for SEC audits.

A healthcare provider integrates Fact0 with an AI agent that processes patient records, ensuring HIPAA-compliant access logs and chain-of-custody.

An e-commerce company runs a customer support AI agent; Fact0 captures all conversations and actions to prove no personally identifiable information (PII) was mishandled.

A software engineering team deploys an AI agent that automatically submits pull requests; Fact0 creates a verifiable trail of all code changes for compliance reviews.

A procurement department uses an AI agent to negotiate with suppliers; Fact0 logs all offers and acceptances to create a non-repudiable audit for financial audits.

A government agency employs an AI agent to process FOIA requests; Fact0 ensures the decision process is transparent and auditable by oversight bodies.

What Problem It Solves ▼

Key Features ▼

✓

Cryptographically tamper-evident logs ensure integrity and non-repudiation.

✓

Seamless integration with popular AI agent frameworks like LangChain and AutoGPT.

✓

Real-time policy enforcement prevents unauthorized actions before they occur.

✓

Enterprise-grade deployment options (on-premises, cloud) with SIEM integration.

✓

Comprehensive compliance reporting simplifies security reviews and audits.

Overview

Full Description ▼

At its core, Fact0 uses a combination of cryptographic techniques such as SHA-256 hashing, Merkle trees, and public-key infrastructure to create a verifiable chain of custody for every agent interaction. Each event recorded in the audit log is timestamped and linked to previous events, forming an append-only ledger that can be independently verified. This approach provides non-repudiation, ensuring that neither the agent nor the operator can deny actions that took place. Fact0 also integrates with enterprise identity and access management (IAM) systems to track which user or system initiated each agent task, adding an additional layer of accountability.

Beyond logging, Fact0 includes policy enforcement features that allow security administrators to define rules about permitted agent behaviors. If an agent attempts an action outside predefined bounds, the system can block the action and flag it for review. This real-time policy engine helps prevent data exfiltration, unauthorized access, and other security breaches. The audit data can be exported to SIEM systems like Splunk or Elastic for correlation with other security events, making it a seamless part of the enterprise security stack.

Fact0 is built to address the unique challenges of autonomous AI agents, which often chain multiple LLM calls and external tool invocations in unpredictable ways. Traditional logging solutions fall short because they cannot capture the nuanced decision-making process of an agent or provide cryptographic guarantees. Fact0’s agent-aware instrumentation automatically traces multi-step workflows, ensuring that every critical step is captured without requiring developers to manually add logging code. The platform is agent-agnostic, supporting popular frameworks like LangChain, AutoGPT, and custom agent implementations via a REST API or SDK. By providing this comprehensive auditability, Fact0 helps organizations unlock the productivity gains of AI agents while maintaining the trust of security stakeholders.