Solutions
AI product analytics: an agent that reads your PostHog
Product analytics tools capture everything users do, but the insight still has to be dug out by a person: building the funnel, segmenting the cohort, interpreting the experiment. AI product analytics closes that gap. You ask a question about user behavior in plain language, and an AI agent runs the analysis against your real event data and explains what it found.
Inteldo's Product Analyst is that agent. It reads your PostHog data and investigates the questions product teams actually ask: where users drop off in a funnel, which features drive retention, whether an A/B test is conclusive, and which early actions predict long-term activation.
To be clear about what Inteldo is: it works with PostHog, not instead of it. PostHog remains your product analytics platform, capturing events, session replays and experiments. Inteldo adds an investigation layer on top, so answers that used to take an afternoon of dashboard work come back as a cited report.
What an AI product analytics tool should investigate
The valuable product questions are rarely single-metric lookups. "Why do users leave?" touches funnel drop-off, feature adoption and cohort behavior at once. An AI product analytics tool should be able to chain those analyses together the way a product analyst would, and show its reasoning at each step.
The Product Analyst is built for exactly this. It watches what users actually do, not what they say, and turns behavioral data into answers you can act on.
- Conversion funnel analysis: find the exact step where users drop off
- Feature adoption tracking: which features get used and which drive retention
- A/B experiment management: design experiments, analyze results with statistical rigor
- Session replay analysis: behavioral insights from real user sessions
- Activation metrics: identify the early actions that predict long-term retention
Built to work with PostHog, not replace it
PostHog is where your product data lives: event capture, funnels, feature flags, experiments and session replays. Inteldo does not duplicate any of that. The Product Analyst connects to your existing PostHog project and uses it as the source of truth for every analysis.
The division of labor is simple. PostHog collects and stores the behavioral data; Inteldo interrogates it. When you ask "did the new onboarding flow improve activation?", the Product Analyst queries your PostHog funnels and experiments, runs the comparison, and returns an answer with the underlying data cited, so you can verify every number back in PostHog itself.
From funnel drop-off to root cause
Finding a drop-off point is the easy half of the job. The hard half is explaining it, and that usually requires context beyond product events. Did the drop coincide with a traffic mix change? Did the affected users come from a specific channel or device?
This is where a multi-agent platform pays off. The Product Analyst investigates alongside seven other specialists: the Traffic Analyst reads GA4 and Search Console, the Revenue Analyst reads Stripe. One question fans out to the relevant agents in parallel, and the answer connects product behavior to acquisition and revenue instead of stopping at the funnel chart.
Experiments, flags and ongoing monitoring
The Product Analyst goes beyond read-only reporting on experiments. With full PostHog write access, it can create and manage feature flags, design A/B experiments, analyze results with statistical rigor, and recommend whether to ship based on confidence levels.
Answers do not have to be one-offs either. When an investigation surfaces a metric worth tracking, like adoption of a newly shipped feature, you can turn it into a signal board that keeps monitoring it. Connections are OAuth secure and read-only by default, write access is granted only when you authorize it, and Inteldo does not train on your data.