Skip to content
    LangSmith
    LangSmith vs Brizz

    Keep LangSmith.
    Add Brizz on top.

    LangSmith answers what the system did and where it broke technically. Brizz answers whether the agent actually worked. Different layers, different audiences, both useful.

    See Brizz in action→Explore the product
    01positioning

    LangSmith

    LLM observability

    Step by step trace debugging for engineers. LLM as judge evals and experiments. Prompt management. The technical observability layer below the agent.

    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, intent, and journey analytics
    ×
    ✓
    Automatic issue detection with impact scoring
    ●
    ✓
    Agent Health Score
    ×
    ✓
    Built for PM, exec, and builder
    ×
    ✓
    Closed loop, verify the fix worked
    ×
    ✓
    LLM tracing and spans
    ✓
    ●
    Evals and LLM-as-judge
    ✓
    ●
    Full Partial Not offered

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

    03the verdict

    LangSmith tells engineers how the system ran. Brizz tells the whole team whether the agent worked. Keep LangSmith, add Brizz.

    04the rest of the field

    See how Brizz stacks up, across the field.

    Mixpanel vs Brizz
    Mixpanel vs Brizz
    Mixpanel handles events, funnels, and retention beautifully. Brizz handles the new shape of products: conversations, intents, and outcomes that no event ever captures.
    See the breakdown→
    Amplitude vs Brizz
    Amplitude vs Brizz
    Amplitude's Agent Analytics clusters conversations and ties them to product metrics — a capability inside its broad analytics suite. Brizz is the dedicated agent platform that scores agent health and proves the fix worked.
    See the breakdown→
    Pendo vs Brizz
    Pendo vs Brizz
    Pendo's Agent Analytics reads conversations, clusters use cases, and flags issues as one module inside its broader suite. Brizz is built for agents end to end, so it scores each issue's impact, tracks a single health score, and verifies the fix actually worked.
    See the breakdown→
    Langfuse vs Brizz
    Langfuse vs Brizz
    Langfuse is the leading open source LLM engineering platform: OTel native tracing, prompt management, and evals, all self hostable. Brizz is the analytics layer that lives on top. We already integrate.
    See the breakdown→
    See all AI agent analytics comparisons→New to agent analytics? Start here→

    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.

    LangSmith answers what the system did and where it broke technically. Brizz answers whether the agent actually helped users — intents, journeys, issue impact, and a single Agent Health Score.

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

    It's built for engineers — traces, evals, and prompt management. It doesn't detect semantic intents, score agent health, or close the loop on fixes for PMs and the wider team.

    Ready to see what LangSmith can't?

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

    See the integrations→