←Back to Blog
    announcementproduct

    Introducing Brizz: Product Analytics for AI Agents

    Brizz Team·

    Traditional analytics tools were built for a world of buttons, forms, and page views. But when your product is powered by AI agents — chatbots, copilots, autonomous workflows — those metrics don't tell you what's actually happening.

    The Problem with Traditional Analytics

    When a user interacts with your AI agent, what do you measure? Session duration? Thumbs up / thumbs down? Those surface-level metrics don't capture what matters:

    • What did the agent actually do? Did it understand the user's intent? Did it take the right actions?
    • Where does it fail? Not just errors — subtle quality issues, hallucinations, missed intents.
    • What's the business impact? How do agent interactions translate to outcomes your team cares about?

    How Brizz Is Different

    Brizz is purpose-built for AI agent analytics. We analyze every conversation to give product teams, not just engineers, the visibility they need.

    Intent Classification

    Brizz automatically identifies what users are trying to accomplish in each conversation. You see emerging patterns, trending intents, and gaps in your agent's capabilities — without manual tagging.

    Quality Scoring

    Every session gets a quality assessment based on user satisfaction signals, task completion, and behavioral patterns. You know at a glance which conversations went well and which need attention.

    Actionable Alerts

    When something changes — a spike in negative interactions, a new intent pattern, a performance regression — Brizz alerts your team in Slack with context and suggested actions.

    Getting Started

    Integrating Brizz takes minutes. Our SDK is OpenTelemetry-compatible, so it fits into your existing agent infrastructure:

    from brizz import Brizz, start_session

Brizz.initialize(
    api_key='your-brizzai-api-key',
    app_name='my-app',
)

with start_session('session-123') as session:
    session.update_properties(user_id='user-123', model='gpt-4')
    response = openai.chat.completions.create(
        model='gpt-4',
        messages=[{'role': 'user', 'content': 'Hello'}],
    )

    Within minutes of your first session, you'll start seeing insights in your Brizz dashboard.

    Ready to see what your agents are really doing? Get in touch.