AgentOps — Developer platform for AI agent observability and debugging. Best for Teams building multi-agent AI applications requiring observability, Developers debugging complex LLM pipelines with time travel replay, Enterprises needing compliance (SOC-2, HIPAA) for agent deployments. Free to start; paid plans from $40/mo.
Teams building multi-agent AI applications requiring observabilityDevelopers debugging complex LLM pipelines with time travel replayEnterprises needing compliance (SOC-2, HIPAA) for agent deploymentsCost-conscious teams tracking LLM spend across 400+ models
Not ideal for
Simple single-agent chatbots that don't need advanced debuggingTeams on a tight budget with high event volumes (pricing scales with events)Organizations requiring fully transparent enterprise pricing without contactProjects needing extensive integration beyond LLM frameworks (limited integrations listed)
AgentOps is a strong choice for teams needing deep observability and debugging for multi-agent systems. Its 400+ LLM support and time travel replay are standout features, but pricing visibility beyond Pro is limited.
When to pick this: you're building complex multi-agent workflows with CrewAI or Autogen and need granular debugging. The time travel replay is excellent for root-cause analysis. When to pass: simple chatbot or single-LLM apps might be overkill; LangSmith or basic logging suffice. Comparison to alternatives: AgentOps has broader LLM support (400+) than most rivals and unique fine-tuning cost savings. Real-world caveats: event-based pricing can scale costs quickly; enterprise features require a sales call.
Skip AgentOps if Skip AgentOps if you need a no-code agent builder, or if your event volume is low and you can't justify the cost scaling.
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Viability Score
80/100
Safe Bet
How likely is AgentOps to still be operational in 12 months? Based on 6 signals including wrapper dependency, GitHub traction, pricing model, and category risk.
funding runway
80
website health
90
github activity
50
category mortality
70
wrapper dependency
100
hyperscaler overlap
80
About AgentOps
AgentOps is a developer platform for tracing, debugging, and deploying reliable AI agents and LLM applications. Built for engineers building with OpenAI, CrewAI, Autogen, and 400+ LLMs and frameworks, it provides agent observability with visual event tracking, time travel debugging, and full audit trails. Key features include LLM cost tracking across 400+ models, token counting, fine-tuning at up to 25x lower cost, and native integrations with top agent frameworks. AgentOps offers a free tier for up to 5,000 events, a Pro plan starting at $40/month, and enterprise options with custom SSO, on-premise deployment, and compliance certifications like SOC-2 and HIPAA. Compared to alternatives, AgentOps covers the full agent lifecycle from development to production with replay analytics and role-based permissions.
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Key Features
Visual event tracking for LLM calls, tools, and multi-agent interactions
Time travel debugging with point-in-time replay
Full audit trail of logs, errors, and prompt injection
LLM cost tracking across 400+ models
Token count tracking and monitoring
Fine-tune LLMs up to 25x cheaper on saved completions
Session and event export (Pro)
Role-based permissioning (Pro)
Custom SSO (Enterprise)
On-premise deployment (Enterprise)
Custom data retention policy (Enterprise)
Real-world workflow fit
Concrete scenarios for the personas AgentOps actually fits — and what changes day-one when you adopt it.
ML engineer debugging a multi-agent CrewAI pipeline
After deploying a three-agent system for customer support, you notice agents occasionally hallucinate responses. You install the AgentOps SDK, run the agents, and use the replay feature to step through the exact sequence of LLM calls and tool outputs that led to the error.
Outcome: You identify a misconfigured prompt in one agent, fix it, and verify the correction via replay — reducing debugging time from hours to minutes.
Team lead tracking cost across multiple agent deployments
Your team runs 10 different agents using various LLMs (GPT-4o, Claude Opus). You need a unified cost dashboard. You integrate AgentOps, and it automatically attributes every token and cost to each agent, with up-to-date pricing.
Outcome: You identify that one agent using Claude Opus is 40% of total spend. You switch it to a cheaper model, saving $2,000/month without sacrificing quality.
Use Cases
Monitor and debug multi-agent interactions in real-time
Track token usage and costs across multiple agents and LLM calls
Replay past agent runs to diagnose failures or unexpected behavior
Fine-tune LLMs on saved agent completions to reduce costs
Models Under the Hood
GPT-4oClaude OpusGeminiLlama 3Hugging Face models400+ LLMs
Limitations
The free Basic plan caps at 5,000 events per month, which may be limiting for heavy usage. Pro plan pricing is pay-as-you-go starting at $40/month, but costs can scale with event volume. Enterprise features like SSO and on-premise deployment require a custom contract.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Annual total
Free
Over 12 months
Effective monthly
Free
Billed monthly
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published AgentOps tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Basic
$0 per month
Ideal for
Solo developer or small team exploring agent observability with low event volume (<5,000 events/month)
What this tier adds
Free entry point with up to 5,000 events, agent-agnostic SDK, LLM cost tracking, and replay analytics.
Pro
Starting at $40 per month, pay as you go
Ideal for
Growing team with moderate to high event volume needing unlimited events, log retention, and role-based permissions
What this tier adds
Unlimited event limit and log retention, session/event export, dedicated Slack and email support, and role-based permissioning.
Enterprise
Custom pricing, contact for demo
Ideal for
Large organization requiring compliance (SOC-2, HIPAA, NIST AI RMF), on-premise deployment, custom data retention, and SLA
What the public pricing page doesn't put in bold. Captured from pricing-page footnotes, contract terms, and recurring complaints.
•Pro pricing is pay-as-you-go; costs increase with event volume beyond the free tier
•Enterprise features like SSO, on-premise, and compliance require custom pricing
Where the pricing makes sense
The company stage and team size where AgentOps's pricing actually pencils out — and where peers do it cheaper.
AgentOps fits mid-to-high-volume agent teams. The free tier is generous for prototyping but tight for production. Pro starts at $40/month, but event costs can add up — similar to competitors like LangSmith (usage-based). Cheaper alternatives exist for low-volume monitoring (e.g., open-source tools). Enterprise custom pricing is comparable to other compliance-ready observability platforms.
Setup time & first value
How long it actually takes to get something useful out of AgentOps — broken out by persona, not the marketing-page minute.
For engineers: install via pip (`pip install agentops`) and add a few lines of code to your agent script. First events visible in the dashboard within minutes. Full replay and cost tracking operational within an hour.
