Regulated enterprises can't put AI agents in production without evidence of every action, decision, and data access. AgentesPro is the reliability and audit layer that generates that proof — automatically.
Engineering teams get reliability. Compliance teams get evidence. Both from the same tamper-evident trail.
Uptime, error rates, latency, and cost per run for every agent in your fleet. Know an agent is down or looping before your customers do.
Every tool call, LLM call, data access, and decision is SHA-256 hash-chained. Any alteration of the record breaks the chain — evidence, not just logs.
Export a compliance-grade report of any agent decision: what data it accessed, what policy it applied, why it decided, and who approved. Built for auditors, not just developers.
PHI access tracking, policy-violation detection, and human-in-the-loop approval records. Healthcare first — insurance, finance, and legal next.
Drop the SDK into any agent framework. Every action becomes hash-chained evidence, streamed to your dashboard in real time.
from agentespro import AgentesPro ap = AgentesPro(api_key="...", agent_id="prior-auth") with ap.run(task="Review PA-1042") as run: run.log_tool_call("ehr.fetch_patient", data_categories=["PHI"]) run.log_decision("APPROVE", policy_ref="UM-4.2", confidence=0.94) # → tamper-evident audit trail, automatically
Agentic AI is moving into production across healthcare, insurance, and finance — industries where "trust me" is not an acceptable answer to a regulator. The EU AI Act, HIPAA, and state-level automated-decision laws all point the same direction: if an AI system makes decisions about people, you must be able to explain and evidence them. The observability market passed $2B in 2025; the audit layer is the part nobody has standardized yet.