The Problem
SaaS founders deploying AI agents for support, refunds, and data processing have no way to audit what those agents actually do. When an AI bot processes a refund or modifies customer data, there's no permission model, no audit trail, and no way to answer regulators' questions about who approved it—creating serious compliance and legal liability.
What I'm Thinking of Building
AgentAudit captures every action your AI agents take, stores them in an immutable log, and gives you a searchable audit dashboard. Integrate via a single webhook or SDK, set permission rules per agent, and export compliance-ready reports for SOC2, HIPAA, or financial audits. Built for AI-native teams, not legacy IAM systems.
Who It's For
SaaS founders and ops leads at growth-stage companies (Series A–B, $1M–10M ARR) building AI-powered support, automation, or data-processing features. Especially fintech, healthcare platforms, and B2B SaaS with compliance pressure.
Key Features (Planned)
- Immutable webhook-based action logging for all AI agent calls
- Role-based permission rules: define what each agent can and cannot do
- Searchable audit dashboard: filter by agent, action, date, outcome, affected resource
- Compliance-ready exports: SOC2, HIPAA, and PCI-DSS report templates
- Real-time alerts if an agent attempts actions outside its permissions
- One-line SDK integration: npm install + one environment variable
I'm validating this idea before writing a single line of code. If this resonates with you, I'd love your feedback:
If you're running AI agents in production right now, how are you currently tracking what they do and proving it to customers or regulators?
Check out the concept page and let me know what you think.
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