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Athina AI vs OpenObserve

Athina AIOpenObserve

Bottom line: Athina AI for lLM app developers; OpenObserve for teams running agents in production.

Athina AIAthina AI

Observability, evaluation, and experimentation platform for LLM teams

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OpenObserveOpenObserve

OpenTelemetry-native observability for LLM calls, tools, and agent handoffs

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Votes00
PricingFreemiumFreemium
CategoryLlm ObservabilityLlm Observability
Tags
llm-observabilityevaluationmonitoringtracingllm-as-judge
opentelemetryllm tracingagent observabilitytoken costopen source
Best for
  • LLM app developers
  • AI/ML teams
  • Prompt engineers
  • Teams running agents in production
  • Platform teams already using OpenTelemetry
  • Organisations needing LLM cost attribution
Pros
  • Combines observability and evaluation
  • 50+ preset evals plus custom and LLM-as-judge
  • Full trace capture with execution replay
  • Segmented analytics across many dimensions
  • Self-hosted VPC and SOC 2 Type 2 options
  • Agent traces are standard OpenTelemetry spans, not a silo
  • Per-span token cost from your own model pricing
  • Unlimited users with no per-seat charge
  • AGPL-3.0 core with a self-hosted option
  • Self-hosted enterprise free up to 50 GB per day
Cons
  • Requires instrumentation to get value
  • Broad feature set has a learning curve
  • Advanced/enterprise features are paid
  • Overlaps with other eval tools in the market
  • Best suited to technical AI teams
  • LLM observability is labelled preview
  • Online evaluations are an enterprise feature
  • Ingestion-based pricing needs volume forecasting
  • Self-hosting carries operational overhead
  • Payload capture raises data governance questions

Comparison generated from each tool's listing. Add or remove tools above to change it.