LangSmith vs Deepgram

LangSmith

Deepgram

LangSmith · 14 features

• Alerts — Threshold alerts on latency, cost, eval metrics.
• Annotation Queues — Human-review workflows for trace quality rating.
• Custom Dashboards — Aggregate metrics dashboards per project/tag.
• Datasets — Collect examples → use as eval sets or training data.
• Evaluations — LLM-as-judge, embedding similarity, custom Python evaluators, offline batch eval…
• LangChain Integration — Auto-trace any LangChain/LangGraph run with env var.
• LangGraph Integration — First-class trace + eval for LangGraph agents.
• LLM Tracing — Automatic trace every LLM call + tool call + chain step.
• OpenTelemetry Export — Export traces as OTLP to Datadog/Honeycomb/etc.
• Playground — Test prompts + models inline before deploying.
• Prompt Canvas — Visual prompt editor with live test + eval.
• Prompt Hub — Public + private prompt library with versioning.
• Self-Hosted (Enterprise) — Docker + k8s deployment in your infra.
• Threads + Sessions — Group traces into conversational sessions.

Deepgram · 15 features

• Aura TTS — Low-latency text-to-speech (<250ms).
• Data Residency — EU / US / custom regions.
• Diarization — Speaker identification.
• Intent Detection — Detect speaker intents automatically.
• Keyterm Prompting — Boost accuracy for proper nouns + domain terms.
• Language Detection — Auto-detect spoken language.
• On-Prem Deployment — Enterprise: run Deepgram in your infra.
• PII Redaction — Auto-redact sensitive info.
• Pre-recorded STT — Transcribe audio/video files.
• Sentiment Analysis — Per-segment sentiment scores.
• Smart Format — Numbers, dates, times auto-formatted.
• Streaming STT — Realtime WebSocket-based transcription.
• Summarization — Automatic transcript summaries.
• Topic Detection — Auto-extract conversation topics.
• Voice Agent API — Unified STT + LLM + TTS for voice bots.