AI agent analytics tools, compared.
Three categories of tools claim a piece of agent analytics — LLM observability stacks, product analytics suites, and dedicated agent platforms. Here is how each compares to Brizz, side by side and honestly.
LLM observability (LangSmith, Langfuse) traces what the system did, for engineers. Product analytics (Mixpanel, Amplitude, Pendo) reads clicks and events, and is now bolting on agent features. Neither was built to read the conversation as the unit of analysis, score an agent's health, and verify a fix actually worked. Agent analytics is the layer that does — and it is what Brizz is built for. What is agent analytics? →
All six tools, scored side by side.
The capabilities an agent analytics buy actually turns on, scored across all six tools — including what each rival does better than Brizz.
Swipe the table to see all six →
| Capability |  brizzAgent analytics | MixpanelProduct analytics | AmplitudeProduct analytics | PendoDigital adoption suite | LangSmithLLM observability | LangfuseOpen-source LLM observability |
|---|---|---|---|---|---|---|
| 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 | ✓ | × | × | × | × | × |
| Stronger at | The five rows above | Product funnels, retention, and event analytics | Ties agent quality to revenue and retention | Product adoption and retention dashboards · Ties agent quality to revenue and retention | LLM tracing and spans · Evals and LLM-as-judge | LLM tracing and spans · Evals and LLM-as-judge · Open source and self-hostable |
Reviewed quarterly against each vendor's public docs
Product analytics suites, adding agent features.
Mixpanel runs your product analytics. Brizz runs your agent analytics.
Stronger at: Product funnels, retention, and event analytics
Amplitude reads agent conversations as one capability inside a broad suite. Brizz is the dedicated agent analytics platform — deeper on every conversation, and the only one that proves the fix worked.
Stronger at: Ties agent quality to revenue and retention
Pendo measures whether your agent gets used. Brizz shows why it fails, and proves you fixed it.
Stronger at: Product adoption and retention dashboards · Ties agent quality to revenue and retention
LLM observability stacks, built for engineers.
LangSmith surfaces the patterns and failure modes. Brizz scores them against one Agent Health Score and proves the fix worked. Keep LangSmith, add Brizz.
Stronger at: LLM tracing and spans · Evals and LLM-as-judge
Langfuse is the builder's tracing and eval stack. Brizz is the analytics layer on top. Keep Langfuse, add Brizz.
Stronger at: LLM tracing and spans · Evals and LLM-as-judge · Open source and self-hostable
Rival vs rival. Where Brizz fits.
Which problem are you actually solving?
Debugging the runtime?
Keep your tracing and eval stack for engineers, and layer Brizz on top to read intent, journeys, and outcomes for the whole team.
Measuring product usage?
Keep your product analytics suite for events, funnels, and retention — and add Brizz for the conversations they can't read.
Improving the agent itself?
That's agent analytics: a single Agent Health Score, impact-scored issues, and closed-loop proof the fix worked. That's Brizz.
Agent analytics, answered
Agent analytics reads every AI agent conversation as the unit of analysis — detecting user intents and journeys, auto-classifying issues by their impact on agent health, and verifying that fixes actually worked. It's distinct from product analytics (events) and LLM observability (traces). Learn more →
It depends on the job. LLM observability tools (LangSmith, Langfuse) trace the runtime for engineers; product analytics suites (Mixpanel, Amplitude, Pendo) read events and are adding agent features. Brizz is the dedicated agent analytics layer that reads meaning and outcomes for the whole team.
No. Keep your observability and product analytics stack. Agent analytics adds the conversation layer they weren't built for — most teams run Brizz alongside an existing tool.
Start with the tool you already use or are evaluating. If you're choosing between two rivals, the head-to-head pages (LangSmith vs Langfuse, Mixpanel vs Amplitude) show where each wins and where Brizz fits.
See it on your own agents.
Brizz turns every agent conversation into intel your whole team can act on.