The first performance warranty platform for autonomous AI agents — guaranteeing uptime, response time, and reliability. Deploy agents into business-critical workflows with a concrete safety net.
Companies deploying autonomous AI agents into critical workflows face unquantified risk with no safety net — unlike cloud infrastructure, which has decades of SLA maturity.
AI agent failure costs companies $5K–$500K per major incident — customer compensation, rework, legal fees, and reputation damage. Yet unlike cloud services, no product offers a performance guarantee for AI agents.
AWS, Azure, and GCP SLA guarantees cover infrastructure uptime — server availability, network connectivity. They say nothing about whether your AI agent is responding accurately, on time, or at all.
Without performance guarantees, companies limit AI agents to reversible, low-stakes tasks. The highest-value agent deployments — contracts, refunds, trades — remain out of reach.
From instrumenting your agent to receiving your first credit — a process designed to be simple enough for any AI ops team.
Add 5 lines of Python to your agent. Our SDK starts reporting availability and response times immediately — no infrastructure changes required.
Our 2-week baseline assessment measures your agent's natural performance profile. This becomes the benchmark against which warranty violations are detected.
When your agent's performance drops below warranty thresholds, credits are automatically calculated and applied to your next invoice — or paid out via Stripe.
Our Python SDK instruments your agent in minutes. Works with LangChain, AutoGPT, custom agents, and any LLM-powered system.
# agentsure/integrate.py — add to your agent entrypoint from agentsure import monitor # Initialize with your API key monitor.start( api_key="as_live_xxxxxxxxxxxxxxxx", agent_id="support-bot-prod", flush_interval=300 # seconds between reports ) # That's it. Baseline starts automatically.
Start with Bronze and upgrade to Silver as your agent fleet grows. Gold tier (with accuracy guarantees) launches after our 6-month actuarial data collection period.
No setup fees. No minimums. Cancel anytime. Volume discounts available for 10+ agents.
Join 200+ companies who have instrumented their agents and are protecting their deployments with AgentSure warranties.
Complete the 2-week baseline assessment to establish your agent's performance profile, then activate your warranty tier.
Automatic credits issued when warranty thresholds are breached. Paid out via Stripe or applied to your next invoice.
| Date | Event | Agent | Amount | Status |
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Lightweight Python instrumentation for AI agent performance monitoring. 5 lines to integrate, zero infrastructure changes, works with any LLM-powered agent.
Install via pip:
pip install agentsure-sdk
Add these 5 lines to your agent's entrypoint. The SDK automatically starts baseline collection on first run.
# agentsure/integrate.py from agentsure import monitor monitor.start( api_key="as_live_xxxxxxxxxxxxxxxx", agent_id="support-bot-prod", flush_interval=300 # seconds between telemetry flushes )
The monitor.start() call accepts the following options:
| Option | Type | Default | Description |
|---|---|---|---|
| api_key | string | required | Your AgentSure API key from the dashboard |
| agent_id | string | required | Unique identifier for this agent instance |
| flush_interval | int | 300 | Seconds between telemetry flushes to AgentSure (min: 60, max: 3600) |
| custom_thresholds | dict | null | Override warranty thresholds (uptime_pct, p95_ms) |
| log_level | string | "info" | Logging level: "debug", "info", "warn", "error" |
| tags | dict | {} | Custom tags for filtering in the dashboard (env, region, version) |
The SDK automatically collects and reports the following metrics to AgentSure:
| Metric | Type | Description |
|---|---|---|
| availability | float | 1.0 when agent is responding, 0.0 when unavailable (heartbeat check) |
| response_time_ms | int | End-to-end response time for each agent task in milliseconds |
| request_count | int | Number of requests processed in the flush interval |
| error_count | int | Number of failed or timed-out requests in the flush interval |
| custom_metrics | dict | User-defined metrics via monitor.report(metric_name, value) |
t.agentsure.io. For air-gapped deployments, contact us about on-premise telemetry collectors. Verify your API key is correct and not expired in the dashboard under Settings → API Keys.| Claim ID | Type | Date Filed | Agent | Status | Resolution |
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