Trace, replay, and evaluate AI agent sessions
Advisor score
Documented editorial evaluation
The decision
AgentOps earns a pilot for agent-heavy teams that need session-level debugging. Approve it only after redaction and retention controls, trace coverage, alert quality, unit economics, and time-to-root-cause beat existing telemetry.
Best for
Teams debugging multi-step agents; Agent cost and latency analysis.
Choose something else if
Simple single-call applications; Sensitive traces without redaction
Evidence
Editorial research pending · 8.2/10
Pricing checked
See current vendor pricing · 2026-09-13
Free access is available, with limits.
Yes. Basic includes up to 1,000 events.
Community choice
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AgentOps is an observability platform for recording agent sessions, tool calls, model costs, errors, latency, replays, and evaluation signals.
AgentOps earns a pilot for agent-heavy teams that need session-level debugging. Approve it only after redaction and retention controls, trace coverage, alert quality, unit economics, and time-to-root-cause beat existing telemetry.
Instrument 200 sessions with seeded tool errors, loops, slow calls, hidden retries, prompt injection, sensitive fields, and incorrect success states. Measure trace completeness, redaction, overhead, cost attribution, replay accuracy, diagnosis time, retention, and event consumption.
Personal Recommendation
AgentOps earns a pilot for agent-heavy teams that need session-level debugging. Approve it only after redaction and retention controls, trace coverage, alert quality, unit economics, and time-to-root-cause beat existing telemetry.
Try the recommendation
Agent-focused replay model
Overall Score
Editorial Review Framework
Overall Score
8.2
Ease of Use
8.0
AI Quality
8.0
Features
8.4
Speed
8.0
Integrations
8.2
Value for Money
8.2
Customer Support
7.6
Learning Curve
7.6
Recommended Because…
Agent-focused replay model
Scores use a 0-10 editorial scale: 9–10 exceptional, 8–8.9 strong, 7–7.9 capable with material tradeoffs, 6–6.9 limited fit, and below 6 not recommended. Scores publish only when a documented evaluation supports them.
Reusable trial worksheet
Turn this review’s buyer test into evidence. Your entries autosave only in this browser and are never added to shared shortlist links.
Confirm the tool meets every must-have workflow and stakeholder requirement.
Review starting point: Teams debugging multi-step agents; Agent cost and latency analysis; Organizations needing session replay
Run the same representative work you would use in production; do not score a polished demo.
Review starting point: Complete three to five representative tasks with known acceptable outcomes and compare them with your current process.
Calculate the effective cost per accepted result, including usage, review, corrections, and required add-ons.
Review starting point: Basic is free for up to 1,000 events. Pro starts at $40 per month for up to 10,000 events and adds unlimited retention, exports, permissions, and support. Enterprise pricing is custom and can include SSO, self-hosting, custom retention, and SLAs. Reviewed September 13, 2026.
Define an acceptance threshold, test known answers and edge cases, and record every correction.
Review starting point: Editorial quality signals: features 4.2/5; AI quality 4.0/5. Validate these signals in your own work.
Verify what data enters the product, who can access it, how long it is retained, and whether it trains models.
Review starting point: Use approved low-risk data first. Check roles, consent, deletion, subprocessors, model-training settings, and the contract—not only the marketing page.
Test the real handoffs, permissions, failure states, and export path your team depends on.
Review starting point: CrewAI, AutoGen, LangChain, OpenAI, Python, TypeScript
Record training, governance, reliability, accessibility, ownership, and change-management risks before rollout.
Review starting point: Event counts can rise quickly; Traces may capture sensitive payloads; Automated evaluations require calibration
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Evaluation
Research-based
Price posture
From $0/month
Reviewed
2026-09-13
No authentic product screenshot is published for this review. DiscoverAI does not use generated interface images as product evidence.
Editorial freshness
Pricing and material product claims were checked September 13, 2026.
Community evidence
Structured, editor-moderated experience—not star ratings. This complements our independent review and never changes its score.
No approved community evidence yet. Be the first verified user to contribute.
AgentOps is an observability platform for recording agent sessions, tool calls, model costs, errors, latency, replays, and evaluation signals.
Basic is free for up to 1,000 events. Pro starts at $40 per month for up to 10,000 events and adds unlimited retention, exports, permissions, and support. Enterprise pricing is custom and can include SSO, self-hosting, custom retention, and SLAs. Reviewed September 13, 2026.
Teams debugging multi-step agents, Agent cost and latency analysis, Organizations needing session replay.
Instrument 200 sessions with seeded tool errors, loops, slow calls, hidden retries, prompt injection, sensitive fields, and incorrect success states. Measure trace completeness, redaction, overhead, cost attribution, replay accuracy, diagnosis time, retention, and event consumption.
Keep Deciding
How to Set AI Spend Caps Before Costs Drift
Set AI budgets at the workflow level, not only the company level. Define a maximum cost per accepted outcome, daily and monthly ceilings, alerts below the hard limit, per-user or service quotas, model-routing rules, retry and loop limits, concurrency controls, and human approval before expensive or high-volume jobs.
How to Monitor an AI Workflow After Launch
Monitor AI workflows at three levels: technical health such as latency, errors, and spend; output quality such as acceptance, correction, citations, and severe failures; and business outcomes such as resolution, conversion, or cycle time. Assign an owner, alert thresholds, an incident path, and a tested rollback before launch.
AgentOps Review 2026: Agent Tracing, Pricing, and Limitations
AgentOps is an observability platform for recording agent sessions, tool calls, model costs, errors, latency, replays, and evaluation signals.
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