AI-ROS monitors your inference pipelines, tracks latency and uptime contracts at the model endpoint level, and triggers remediation before a degraded model call becomes a customer-facing breach.
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APM tools weren't built for AI failure modes
Token throttling, cold model starts, orchestration cascades, and hallucination-driven retries don't map to HTTP 5xx. Your existing observability stack silently misses them.
You're discovering SLA breaches in the postmortem
By the time an AI latency spike triggers a Datadog alert or a customer complaint arrives, the breach window has already passed. There is no active enforcement layer.
Reliability is still a manual contract
SLA commitments live in a doc. Enforcement happens in retros. On-call engineers spend incident hours debugging inference layers that have no native tooling for reliability contracts.
AI-ROS is designed for teams that need reliability contracts enforced at the infrastructure layer, not tracked in a spreadsheet after the fact.
Connect your AI stack
Native integration with your inference provider (OpenAI, LangChain, or AWS Bedrock). One SDK import or sidecar — zero infrastructure change required.
Define your SLA contracts
Set p50/p95/p99 latency thresholds and uptime targets per endpoint, route, or model. Contracts live in code, version-controlled alongside your infra.
Monitor, alert, remediate
AI-ROS tracks every inference call against your contracts in real time, fires breach alerts before customers notice, and triggers remediation playbooks automatically.
Not APM retrofitted for AI. Every feature is designed around the specific reliability contracts your inference pipelines need to hold.
Latency and uptime thresholds that actually enforce
Define p50/p95/p99 targets per model endpoint. AI-ROS tracks adherence in real time, not in the postmortem.
Alerts tuned for inference failure modes
Token quota exhaustion, cold start degradation, and orchestration retries fire alerts before they compound into a customer SLA breach.
Automated response, not just a PagerDuty ping
Route to a fallback model, throttle downstream callers, or trigger a scale-out — defined once, applied automatically when breach conditions are met.
End-to-end tracing across your inference chain
Track latency and error budgets through model endpoints, orchestration layers, and downstream dependencies in a single view.
Built for engineers getting paged at 2am, not observability dashboards.
AI-ROS follows the same engineering values as the infrastructure it monitors: precision over noise, actionable alerts, and reliability before features.
We're onboarding a small cohort of ML/AI platform teams for early access. If your team has AI in production and no dedicated reliability contract, reach out.
No spam. No pitch deck. Engineering-first conversation.