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The operating system for your AI. Traces, experiments, flags, security — one event stream, everything connected.

Trace: support-pipelinePASSED
coordinator.run()
3.1s
researcher.query()
1.0s
tool.web_search()
0.4s
writer.draft()
0.9s
reviewer.check()
0.5s
tool.respond()
0.2s

SOUND FAMILIAR?

AI agents fail differently.
You need a new kind of observability.

Trace: support-pipelineFAILED
0s0.8s1.6s2.4s
coordinator.run()
2.4s
researcher.query()
0.7s
writer.draft()
ERROR
reviewer.check()
Error: writer.draft() — TimeoutError: LLM call exceeded 30s limit
01

Invisible failures

When a 4-agent pipeline fails at step 3, you need to see the exact handoff that broke — not grep through logs across services hoping to find a clue.

IMPACT

63% of multi-agent failures go undetected for over 24 hours. By the time your team notices, users have already churned.

WITHOUT AGENT OS

Grep logs across 4 services. Check each agent individually. Correlate timestamps manually. Hope you find it before the next standup.

WITH AGENT OS

One click. Full trace. The exact span where the handoff failed, with inputs, outputs, and the error message. Fixed in minutes.

Cost / Day↑ 340%
Which agent is burning your budget?
02

Runaway costs

One agent quietly consumes 10x the tokens of every other agent combined. Your monthly bill tells you the total — but never which agent caused it.

IMPACT

Unpredictable cost is the #1 reason agentic AI projects get cancelled by leadership. Gartner, 2025.

WITHOUT AGENT OS

End-of-month surprise. $4,000 bill. No idea which agent, which model, or which prompts consumed the most. No way to set limits.

WITH AGENT OS

Per-agent, per-model cost breakdown in real time. Budget alerts before they spike. Know exactly where every dollar goes.

Delegation ChainLOOP DETECTED
Coordinator
Researcher
Writer
Coordinator
3
cycles detected
4,200
tokens burned
$1.26
wasted cost
03

Delegation loops

Agent A delegates to B, B delegates to C, C delegates back to A. The cycle repeats silently, burning thousands of tokens with no output.

IMPACT

A single undetected loop can burn $50+ in API costs in under a minute. No existing observability tool detects delegation cycles.

WITHOUT AGENT OS

Your API bill spikes. You notice hours later. You can't tell if it's legitimate load or a loop. There's no tool that even checks for this.

WITH AGENT OS

Automatic DFS cycle detection across the delegation chain. Amber warning fires the instant a loop is detected. Configurable depth limits.

Eval Score — 30 days↓ 23%
Quality dropped. Nobody noticed.
04

Silent regressions

A teammate updates a system prompt. Eval scores drop 23% overnight. Users start complaining about quality — your team finds out from support tickets.

IMPACT

The average time to detect a prompt regression is 3.2 days. By then, user trust has already eroded.

WITHOUT AGENT OS

No baseline. No monitoring. No alert. You learn about quality drops from angry customers, not from your tooling.

WITH AGENT OS

Continuous eval scoring against baselines. Alert fires within minutes of a regression. Automatic diff shows exactly which prompt change caused it.

Prompt Comparison
Prompt v3 — concise???
Prompt v4 — detailed???
Which is better? No way to know.
05

Shipping blind

Your new prompt seems better in manual testing. But 'seems better' isn't data. Without controlled experiments, you're gambling with production quality.

IMPACT

78% of teams ship prompt changes with zero statistical validation. Most don't even know what their current success rate is.

WITHOUT AGENT OS

Manual testing with 5 examples. 'Looks good to me.' Ship to production. Cross fingers. Find out from users if it was actually worse.

WITH AGENT OS

Controlled A/B experiments with traffic splitting. Statistical significance calculated automatically. Guardrails prevent shipping regressions.

Agent OutputPII LEAK
Your SSN is 483-29-●●●●
Sent to user. Discovered 3 days later.
06

Security gaps

Your agents handle customer data, API keys, and sensitive information. A single prompt injection or PII leak can mean regulatory fines and lost trust.

IMPACT

EU AI Act enforcement begins 2026. Organizations face fines up to 7% of global revenue for non-compliance.

WITHOUT AGENT OS

No input validation. No output scanning. PII leaks discovered days later. Prompt injections succeed silently. Jailbreaks go unlogged.

WITH AGENT OS

Real-time input/output scanning. PII auto-redaction. Prompt injection blocking. Every security event logged with full trace context.

Agent OS was built to solve all six — from day one.

One platform. Not six.

Most teams stitch together 4-6 separate tools. Here, everything connects through one event stream.

Traces01

Every LLM call, tool use, and agent handoff — reconstructed as a navigable span tree.

Dashboards02

Cost, latency, error rates across all agents. Click any data point to drill into the trace.

Experiments03

A/B test prompts, models, and configs with built-in statistical significance.

Feature Flags04

Gradual rollouts targeted by user segment or agent type. Instant kill switches.

Security05

Prompt injection, PII detection, and jailbreak blocking — in real time.

Funnels06

Map multi-step agent workflows. See where they drop off and why.

All connected through one unified event stream

Stop flying blind.
See everything.

We're onboarding founding teams one at a time. Three lines of code. Five minutes to your first trace.

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5 min setup

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We review every request within 48 hours.