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security
Rakshex

Rakshex vs LangSmith

LangSmith excels at LLM observability and debugging. But it stops there — no security scanning, no compliance, no kill switch. Rakshex covers observability plus the full security and governance layer teams need once they ship AI to production.

FEATURELANGSMITHRAKSHEX
LLM ObservabilityComprehensive (traces, runs, feedback)Full observability + cost anomaly detection
Security ScanningNot available — observability onlyOWASP API Top 10 + prompt injection blocking
Thinking Token AttributionNot availableFirst-in-world: isolates reasoning tokens (o1/o3/Claude)
PCI DSS ComplianceNot availablePCI DSS v4.0.1 mapped findings + export
Kill Switch / Budget CapNot availableHard stop on budget, anomaly, or red-team score
PII RedactionManual masking onlyReal-time auto-redaction in request/response
Shadow API DetectionNot availableStatic + runtime undocumented endpoint discovery
Cost Attribution per AgentPer-run cost loggingPer-agent, per-model, per-thinking-token breakdown
VS Code ExtensionNot availableIn-editor scanning + inline security warnings
Compliance ReportsNot availableSOC 2, PCI DSS, OWASP — JSON/CSV/PDF export

When to choose LangSmith

  • • You only need LLM run tracing and debugging
  • • You are deep in the LangChain ecosystem
  • • Security and compliance are handled separately
  • • You do not need kill switch or budget caps

When to choose Rakshex

  • • You need security + observability in one platform
  • • You handle PII, financial data, or health records
  • • You want thinking token attribution (o1/o3/Claude)
  • • You need PCI DSS or SOC 2 compliance evidence
  • • You want a kill switch that actually halts traffic
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