Platform Comparison
Document: COMPARE-2025 • Platforms analyzed: 4

How EvalOps compares to
other evaluation platforms

Honest comparison with LangSmith, Weights & Biases, Arize, Humanloop, and other evaluation platforms. We'll tell you when competitors fit better.

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Key Differentiators

What makes EvalOps different

Feature
EvalOps
Others
Pre-release evaluation gates
Built-in
Manual or not available
Compliance & attestations
SOC 2, ISO 27001, EU AI Act
Not available
Framework support
Agnostic
Varies by platform
CI/CD integration
Native gates
API-based or webhooks
Multi-step agent tracing
Full workflows
Limited or prompt-only
Deployment options
SaaS, Dedicated, Private Cloud
Typically SaaS only
Audit trail
Cryptographically signed
Basic logs
External verification
/verify page for auditors
Not available
Platform Analysis

Honest competitor breakdown

COMP-001

LangSmith

LangChain observability platform

EvalOps Advantage

EvalOps is framework-agnostic and designed for governance-first workflows with built-in CI/CD gates and attestation tracking.

COMP-002

Weights & Biases

ML experiment tracking and model registry

EvalOps Advantage

EvalOps focuses on production evaluation loops, not training experiments. Built for teams shipping AI systems, not training models from scratch.

COMP-003

Arize AI

ML observability and monitoring

EvalOps Advantage

EvalOps combines pre-release evaluation gates with production monitoring, and integrates directly into CI/CD pipelines to catch regressions before deploy.

COMP-004

Humanloop

Prompt management and evaluation

EvalOps Advantage

EvalOps captures full agent execution traces (prompts + tool calls + decisions), supports compliance workflows, and provides governance attestations for regulated environments.

Decision Framework

Choose EvalOps when you need
audit-grade governance

When EvalOps wins

  • You need governed evaluation gates in CI/CD
  • You operate in regulated industries and require attestations
  • You run multi-step agents or orchestration beyond prompt → completion
  • You need audit-ready telemetry across providers

When competitors fit better

  • LangSmith: You're all-in on LangChain prototyping
  • Weights & Biases: You're focused on training ML models from scratch
  • Arize: You only need post-deployment monitoring
  • Humanloop: You're iterating prompts with human labeling loops
Discuss your requirements

This comparison reflects our honest assessment as of 2025. Contact us for updates or corrections.