Agnost AI – Analytics for Conversational Text/Voice Agents
Agent analytics in minutes, but metrics dashboards for LLM apps are crowded (Helicone, Langtrace, LangSmith).

Finally sees the bot traffic GA4 filters out, with citation attribution.
Website owners, SEO specialists, SaaS founders
Google Analytics · Cloudflare Bot Fight Mode · Fingerprint
It's mainly due to most analytic tools (like GA4, Mixpanel, Amplitude) reply on a JS snippet that fires in a browser. But AI agents don't load JS. They hit your server, read the HTML, and leave. The only place they show up is in raw server logs.
So we built Arrivl. It works off server logs to show you which agents visited, what pages they read and whether they bring you real human visit. It also runs an audit of how AI friendly your site is and tells you how to improve in an afternoon.
It's completely free with no credit card required. https://arrivl.ai Install is a snippet or a log forwarder, takes a few minutes.
Would love some feedbacks from the community here.
Agent analytics in minutes, but metrics dashboards for LLM apps are crowded (Helicone, Langtrace, LangSmith).
Hash-chained action logs prove what AI agents actually did, not what they claimed.
Local proxy enforcing markdown rules on LLM output before it hits production.
Live feed of crawler user agents hitting HN right now.
Cedar-inspired DSL + W3C DID + hash-chained logs verify agent compliance deterministically.
Config-as-code YAML for AEO monitoring beats manual spreadsheet tracking for agencies.