AgentOps

Name: AgentOps
Brand: AgentOps

AI Native

AgentOps is an observability, debugging, and cost-tracking platform that records event-level traces of LLM-powered agent executions, provides session replay and audit trails, and reports token usage and model spend across providers.

Est 2023|Raised $2.6M|3 Ref Customers

LinkedIn 7K|Web traffic 69K|FTEs 468

MarketsLLM Observability

01Competitive Landscape

Narrative analysis

AgentOps vs Langfuse - Langfuse's differentiator is a clear open-source self-hosting story and prompt-management workflows. This is attractive for buyers that prioritize full platform self-hosting and internal control. - AgentOps emphasizes agent-specific concepts such as session replay and tool-call tracing and presents an agent-focused debugging and audit narrative. - For prompt version management and experimentation as a primary workflow, Langfuse's positioning is more explicit. AgentOps vs LangSmith - LangSmith may be a natural choice for teams standardized on LangChain/LangGraph due to first-party integration benefits. - AgentOps is positioned as framework-agnostic with agent-centric features. AgentOps vs Helicone - Helicone emphasizes gateway/proxy capabilities and request-level analytics. - AgentOps emphasizes agent run tracing and replay for multi-step agent workflows.

Adoption trends (with caveats)

Public-facing marketing references numeric claims and phrases indicating usage; these are presented as vendor-provided data and are not independently verified in this report.
Press coverage references platform traction in general terms; independent verification of claimed user/customer counts was not available in the public materials reviewed.

	AgentOps	Langfuse	Arize (AX / Phoenix)
Starting Price	Basic: free tier with an event cap; Pro: monthly pay-as-you-go tier; Enterprise: custom	Cloud: free hobby tier and paid tiers; self-host and OSS options available	Phoenix: OSS entry point; AX offers free and paid tiers with enterprise options
Primary use case	Agent-specific production debugging (session replay/time-travel), cost tracking, multi-agent visibility	Teams wanting open-source flexibility, prompt workflows, and self-host option	Teams combining tracing + evals and broader AI observability, with an OSS Phoenix entry point
Key Strength	Session replay/time-travel and agent-focused visualization; multiple integrations listed	Open-source and self-host options; prompt and collaboration workflows	Strong evaluation and observability tooling, OSS entry via Phoenix
Key Weakness	Limited verified reviews on major platforms; public-facing security artifacts not detailed; integration churn risk	Self-hosting operational burden; enterprise-grade features may require paid tiers	Platform complexity for smaller teams; pricing/limits can be less predictable

01Competitive Landscape

Narrative analysis

AgentOps vs Langfuse

Langfuse's differentiator is a clear open-source self-hosting story and prompt-management workflows. This is attractive for buyers that prioritize full platform self-hosting and internal control.
AgentOps emphasizes agent-specific concepts such as session replay and tool-call tracing and presents an agent-focused debugging and audit narrative.
For prompt version management and experimentation as a primary workflow, Langfuse's positioning is more explicit.

AgentOps vs LangSmith

LangSmith may be a natural choice for teams standardized on LangChain/LangGraph due to first-party integration benefits.
AgentOps is positioned as framework-agnostic with agent-centric features.

AgentOps vs Helicone

Helicone emphasizes gateway/proxy capabilities and request-level analytics.
AgentOps emphasizes agent run tracing and replay for multi-step agent workflows.

Adoption trends (with caveats)

Public-facing marketing references numeric claims and phrases indicating usage; these are presented as vendor-provided data and are not independently verified in this report.
Press coverage references platform traction in general terms; independent verification of claimed user/customer counts was not available in the public materials reviewed.

	AgentOps	Langfuse	Arize (AX / Phoenix)
Starting Price	Basic: free tier with an event cap; Pro: monthly pay-as-you-go tier; Enterprise: custom	Cloud: free hobby tier and paid tiers; self-host and OSS options available	Phoenix: OSS entry point; AX offers free and paid tiers with enterprise options
Primary use case	Agent-specific production debugging (session replay/time-travel), cost tracking, multi-agent visibility	Teams wanting open-source flexibility, prompt workflows, and self-host option	Teams combining tracing + evals and broader AI observability, with an OSS Phoenix entry point
Key Strength	Session replay/time-travel and agent-focused visualization; multiple integrations listed	Open-source and self-host options; prompt and collaboration workflows	Strong evaluation and observability tooling, OSS entry via Phoenix
Key Weakness	Limited verified reviews on major platforms; public-facing security artifacts not detailed; integration churn risk	Self-hosting operational burden; enterprise-grade features may require paid tiers	Platform complexity for smaller teams; pricing/limits can be less predictable