AgentOps
Monitoring and observability platform for AI agents with cost tracking and performance debugging
- Also known as
- agentops
Available worldwide · Popular in: US
What is AgentOps?
A developer platform providing observability, debugging, and performance tracking for AI agents and language model applications across multiple frameworks and 400+ LLM providers.
AgentOps pricing
Plans, per-tier features and add-ons, dated and linked to live pricing. Pricing changes often; always verify at source before you rely on it.
Free tier for up to 5,000 events; Pro from $40/month
Basic
FreeFree tier with limited event tracking
- events
- 5,000/month
- Agent Agnostic SDK
- LLM Cost Tracking (400+ LLMs)
- Replay Analytics
Pro
Unlimited events with extended features and support
- events
- unlimited
- Unlimited event limit
- Unlimited log retention
- Session and event export
- Dedicated Slack and email support
- Role-based permissioning
Enterprise
Contact salesCustom deployment, support, and compliance
- SLA
- Slack Connect
- Custom SSO
- On-premise deployment
- Custom data retention policy
- Self-hosting (AWS, GCP, Azure)
- SOC-2 compliance
- HIPAA compliance
- NIST AI RMF
What AgentOps does
The capabilities that matter for llm observability, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Architecture model
- Managed cloud saas
- Token cost and latency waterfall charts
- -
- Opentelemetry openllmetry native export support
- -
- Prompt playground and in dashboard replay
- ✓
- Multi step agentic workflow distributed tracing
- ✓
- User feedback score API for thumbs up down tags
- -
- Pii redaction and prompt content masking
- -
- Production ab testing of system prompts
- -
- Automated anomaly detection for rate limits
- -
- Native integration with langchain and llamaindex
- ✓
- SOC2 type ii
- -
- Mit or apache permissive oss license
- ✓
- Pricing model
- Free open source
Platform & deployment
Independently observed- Web
- Cloud / SaaS
- Self-hosted
Integrations (13)
Independently observed- AG2•
- CAMEL•
- CrewAI
- AG2 (AutoGen)
- Agno
- LangGraph
- OpenAI Agents SDK
- Langchain
- Cohere
- LiteLLM
- LlamaIndex
- Llama Stack
- CamelAI
AgentOps FAQ
Common questions about AgentOps, answered from independent, dated evidence.
What is AgentOps?
A developer platform providing observability, debugging, and performance tracking for AI agents and language model applications across multiple frameworks and 400+ LLM providers. It is indexed under Llm Observability.
Source: https://www.agentops.ai
Is AgentOps free?
AgentOps offers a free tier, so you can start without paying. Paid plans start at $40 per month. Pricing changes often, so verify at source before relying on it.
Source: https://www.agentops.ai
What platforms does AgentOps support?
We have confirmed browser-based access to AgentOps. That is the extent of what we could verify from public sources, so it may well offer desktop or mobile clients we have not indexed.
Source: https://www.agentops.ai
Can AgentOps be self-hosted?
Yes. AgentOps can be deployed cloud / SaaS and self-hosted, so it does not have to run on the vendor's infrastructure.
Source: https://www.agentops.ai
What does AgentOps integrate with?
We have confirmed 11 integrations for AgentOps, including CrewAI, AG2 (AutoGen), Agno, LangGraph, OpenAI Agents SDK, Langchain, Cohere and LiteLLM, plus 3 more. This is what we could verify from public sources, so the vendor may support others we have not indexed.
Source: https://www.agentops.ai
What security certifications does AgentOps have?
We have independently confirmed SOC 2 and HIPAA for AgentOps. Certifications we do not list are ones we have not been able to verify from public sources, which is not the same as AgentOps not holding them. Always confirm compliance directly before you rely on it.
Source: https://www.agentops.ai
Where is AgentOps available?
AgentOps is available worldwide. Its primary market is the United States.
Source: https://www.agentops.ai
AgentOps alternatives
Other llm observability we track, ranked by the same independent score.
- LunaryMonitor and analyze AI application performance with real-time insights and enterprise controlmedium · 73%
- TraceloopAn open-source Rust-based LLM gateway providing unified multi-provider access with built-in observabilitymedium · 72%
- Arize PhoenixOpen-source platform for monitoring and evaluating language model applications in productionmedium · 51%
- OpikAn open-source platform for monitoring and evaluating AI applications and agent workflowslow · 29%
- Weights & Biases WeaveMonitoring and tracing for AI agents in production environmentslow · 25%
Compare AgentOps
Side by side against other llm observability, attribute by attribute, with a source on every value.
The vioscaleAI score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for AgentOps, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Security posture | 50 | 0.12 | 6.1 | ✓ |
| Capabilities | 67 | 0.04 | 2.5 | ✓ |
| Pricing transparency | 45 | 0.05 | 2.4 | ✓ |
| Price level | 50 | 0.04 | 2.1 | ✓ |
| Integrations | 31 | 0.04 | 1.4 | ✓ |
| Reliability | 0 | 0.07 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Content
| Attribute | Value | Evidence |
|---|---|---|
| Faq | 7 items | mediumsource · 2026-09-10 · 59% |
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Pricing model: free_open_source · Architecture model: managed_cloud_saas · Mit or apache permissive oss license: Yes · Prompt playground and in dashboard replay: Yes · Multi step agentic workflow distributed tracing: Yes · Native integration with langchain and llamaindex: Yes | mediumsource · 2026-10-12 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 11 | mediumsource · 2026-10-12 · 60% |
Market
| Attribute | Value | Evidence |
|---|---|---|
| Availability | PrimaryMarkets: … · AvailabilityScope: global · AvailableCountries: … · NotAvailableCountries: … | mediumsource · 2026-08-25 · 50% |
Pricing
Security
Is AgentOps the right choice for you?
Tell us the job, the constraints and what you weigh most, and we will rank AgentOps against the rest of the llm observability we index, using the same dated evidence weighted your way.
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