Comparison

Cisora vs LangSmith

Both observe AI agents — but for very different reasons. LangSmith helps you build a better model. Cisora helps you keep it under control.

LangSmith is for model performance. Cisora is for governance, security, and compliance. They are complementary, not competing — most teams running real agents need both.

Feature comparison

FeatureCisoraLangSmith

LLM call tracing

YesYes

Tool & function call tracing

YesYes

Prompt versioning + evals

Cisora focuses on production, not model dev

PartialYes

Dataset management for fine-tuning

NoYes

Real-time policy enforcement (inline block)

Block unsafe actions in <5ms

YesNo

OWASP LLM Top 10 incident detection

YesNo

NHI / credential scanning across agents

YesNo

Compliance reports (SOC 2, ISO 42001, EU AI Act)

YesNo

Human-in-the-loop review queue

YesNo

Multi-agent inventory + risk scoring

YesPartial

Cost tracking + budget alerts

YesYes

Self-hosted option

Enterprise plan

PartialYes

Vendor-neutral (works with OpenAI, Anthropic, Bedrock, Mistral, anything)

YesYes

Where Cisora is different

Inline policy enforcement, not just observability

Cisora can block an action before it executes — based on deterministic rules you write in our policy DSL. LangSmith observes after the fact.

Security incident detection mapped to OWASP LLM Top 10

Cisora ships with detectors for prompt injection, excessive agency, sensitive info disclosure, model DoS, and more. Findings appear on a governance dashboard, not a developer trace viewer.

Non-human identity (NHI) governance

Every API key, OAuth token, and machine credential your agents touch is fingerprinted and tracked. Rotate stale credentials, detect lateral movement, prove zero-trust posture.

Compliance-grade audit reports

Cisora generates auditor-ready evidence packs for SOC 2, ISO/IEC 42001, EU AI Act, and NIST AI RMF in one click. LangSmith does not target compliance.

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