Cyris

About Cyris

Cyris is a compliance-focused observability tool that captures AI agent decisions and turns them into audit-ready evidence. It auto-instruments connections to more than a dozen LLM providers with minimal integration effort and stores each decision in a tamper-proof, hash-chained audit trail.

Review

Cyris aims to simplify post-hoc verification of AI-driven decisions by automatically logging agent activity and producing shareable artifacts for auditors. The product emphasizes fast setup and practical outputs for compliance teams, such as auto-filled security questionnaires and a live, reviewable trust center.

Key Features

• Automatic instrumentation across 12+ LLM providers with just two lines of SDK code and no manual wiring.
• Tamper-proof, hash-chained audit trail that records each decision entry for forensic integrity.
• Auto-fills security and compliance questionnaires from real operational data in roughly 90 seconds.
• Shareable live trust center URL for external reviewers to inspect compliance posture without account access.
• Forensic trace capabilities to reconstruct full decision chains across agents for debugging or audits.

Pricing and Value

The product page indicates free options are available; detailed commercial pricing is not published publicly. Value is concentrated in time savings for compliance and audit workflows: by producing verifiable evidence automatically, Cyris can reduce the manual effort required for questionnaire responses and post-incident investigations. Teams should evaluate total cost based on their query volumes and retention needs.

Pros

• Very low friction to get started-few lines of code to capture agent activity automatically.
• Strong focus on auditability via a hash-chained, tamper-evident trail rather than plain logs.
• Designed to produce actionable outputs for compliance teams (auto-filled questionnaires, shareable trust center).
• Supports a wide set of LLM providers out of the box, reducing integration work for heterogeneous stacks.

Cons

• Recently launched, so enterprise-grade features, long-term reliability data, and extensive integrations may still be maturing.
• Introducing a centralized audit trail requires careful data governance and privacy review for sensitive workloads.
• Teams may face vendor dependence for audit evidence unless they export and manage copies independently.

Ideal users are healthcare providers, regulated enterprises, and engineering teams running multi-agent AI workflows that must answer audit and compliance inquiries. Cyris is most useful where proving what an AI system did-quickly and verifiably-is a core business requirement.

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