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LangSmith
LangSmith vs Brizz

Keep LangSmith.
Add Brizz on top.

LangSmith reads conversations now too — Insights clusters them into patterns and failure modes, and multi-turn evals score intent and completion. What it still doesn't do is roll that into one score for the agent, or prove a shipped fix actually worked. That's where Brizz picks up.

01positioning

LangSmith

LLM observability

Step by step trace debugging, LLM as judge evals, and prompt management. Its Insights Agent now clusters production traces bottom-up into usage patterns and failure modes with no taxonomy defined up front, and multi-turn evals score semantic intent and task completion across a whole conversation. Reporting stops at the category: error rates and eval scores per cluster, no single score for the agent and no check that a shipped fix held.

brizz

Agent analytics

The analytics layer on top of tools like LangSmith. Reads what users actually wanted, what the agent did about it, and which patterns to fix next. Built for the whole team, not just engineers.

02capabilities

Where the analytics actually live.

The capabilities that decide an agent analytics buy, scored on both sides.

Capability
LangSmith
brizz
Conversation as the unit of analysis
Automatic semantic intent detection
Automatic issue detection with impact scoring
Single Agent Health Score
×
Closed loop, verify the fix worked
×
Built for PM, exec, and builder
LLM tracing and spans
Evals and LLM-as-judge
Full Partial Not offered

Last reviewed September 2026 · from each vendor's public docs

03the verdict

LangSmith surfaces the patterns and failure modes. Brizz scores them against one Agent Health Score and proves the fix worked. Keep LangSmith, add Brizz.

LangSmith vs Brizz, answered

Not exactly — they sit at different layers. LangSmith is trace debugging and evals for engineers; Brizz is the analytics layer on top that reads intents, journeys, and outcomes for the whole team. Most teams keep LangSmith and add Brizz.

Both now read conversations and cluster them by intent and failure mode. The difference is what happens next: LangSmith reports per cluster, while Brizz scores each issue by its impact on a single Agent Health Score and verifies the shipped fix actually resolved it.

Yes. Brizz layers on top of tracing tools like LangSmith, reading the same conversations to surface intents, issues, and the work to prioritize next.

Increasingly. Its Insights Agent clusters production conversations into usage patterns and failure modes automatically, and multi-turn evals score semantic intent and task completion — findings a PM can read. What it still doesn't do is roll those into a single Agent Health Score, weight each issue by its impact on that score, or verify a shipped fix resolved the intent in later conversations.

Ready to see what LangSmith can't?

Brizz turns every agent conversation into intel your whole team can act on.

See the integrations