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Splyntra vs. alternatives

The LLM observability space is full of good tools. Most focus on tracing and evaluation — seeing what an agent did and scoring its output. Splyntra shares that foundation but is built around a different center of gravity: one OpenTelemetry-native pipeline that carries both observability and security signal, with governance and agent identity layered on top.

This page is meant to be factual, not a sales pitch. The tools below are actively developed and add capabilities regularly, so treat the matrix as a snapshot of each product's documented, primary focus — verify current details against each vendor's own docs.

Where Splyntra is different​

  • OpenTelemetry-native, no lock-in. Splyntra ingests OTLP directly and reads the gen_ai.* semantic conventions — there is no proprietary wire format to adopt.
  • One pipeline for trace and security. Secret, PII, moderation, tool-guard, and prompt-injection detection fold into a single risk score on the same spans. This is the main capability the peers below do not center on — they are observability and evaluation tools, not security tools.
  • Governance and agent identity. A hash-chained audit ledger, a policy engine, delegation with spend limits, compliance reports, and OIDC-federated agent identity are part of the platform. These are not typical features of the peers.
  • Source-available, self-host-first. The core is licensed FSL-1.1 and converts to Apache 2.0 two years after each release; the SDKs and integrations are Apache-2.0.
  • Two first-class SDKs. Python and TypeScript, with cost analytics available on every plan.

Capability matrix​

Legend: ✓ = supported · partial = available but not a primary focus, or scoped to a plan/edition · — = not a documented focus.

CapabilitySplyntraLangSmithLangfuseArize PhoenixHeliconeBraintrust
Tracing✓✓✓✓✓✓
OTel-native✓partial✓✓partialpartial
Security / risk detection✓———partial—
Guardrails✓———partial—
Evaluation✓✓✓✓partial✓
Cost analytics✓✓✓partial✓✓
Audit ledger / governance✓—————
Agent identity✓—————
Self-host✓partial✓✓✓partial
Open license✓—✓partial✓—
Python SDK✓✓✓✓✓✓
TypeScript SDK✓✓✓partial✓✓

How each compares​

LangSmith is LangChain's proprietary SaaS for tracing and evaluation. It is mature and tightly integrated with the LangChain/LangGraph ecosystem, and has added OTLP ingestion, though its native model is its own format. If your stack is LangChain-centric and you want first-party support, it's a natural fit. Splyntra differs by being OTel-native regardless of framework and by adding a security and governance layer LangSmith does not focus on.

Langfuse is a popular open-source, self-hostable platform for tracing, evaluation, and prompt management, with OpenTelemetry support and both Python and TypeScript SDKs. It overlaps closely with Splyntra on observability and eval. The distinction is scope: Splyntra folds security detection, an audit ledger, policy, and agent identity into the same pipeline, where Langfuse focuses on observability, evaluation, and prompt engineering.

Arize Phoenix is an open-source, OpenTelemetry-based tool (via OpenInference) for tracing and evaluation, strong on experimentation and analysis. It shares Splyntra's open-standards footing. Splyntra's additions are the unified security/risk pillar and the governance and identity features, which are outside Phoenix's focus.

Helicone is an open-source, proxy-based observability layer that excels at low-friction logging and cost tracking, and offers some prompt-security and moderation features. Its proxy model makes it very easy to adopt. Splyntra takes an instrumentation/OTLP approach instead of a proxy, and goes further into security-risk scoring, governance, and identity.

Braintrust is an evaluation-focused platform, strong on eval workflows, datasets, and experimentation, with logging and OTel ingestion. If evaluation is your primary need, it's well suited to that. Splyntra covers evaluation too, but centers the combined observability-plus-security pipeline and the governance stack.