Solutions
Conversational analytics, answered by AI agents
Conversational analytics means asking questions about your business in plain language and getting answers computed from your real data, not from a dashboard you have to interpret yourself. Instead of building charts, you type a question like "why did signups drop last week?" and the system investigates.
Inteldo takes the idea further than a chat box bolted onto a BI tool. One question fans out to eight specialist AI agents that read your Stripe billing, Google Analytics 4 traffic, PostHog product events and Search Console rankings in parallel, then return a single synthesized answer with every source cited.
What conversational analytics software should actually do
Most conversational analytics tools translate a question into one SQL query against one warehouse table. That works for lookups like "revenue last month" and fails for real business questions, which almost always span several systems at once.
A question like "is the new pricing page hurting conversion?" touches traffic data, product analytics and billing at the same time. Answering it well means correlating all three, which is exactly what a multi-agent approach is built for.
- Understand questions phrased the way an operator asks them, not query syntax
- Reach across data sources: billing, web analytics, product events, search data
- Show its work: cited sources and the reasoning behind every number
- Keep watching: turn one-off answers into signal boards that monitor the metric
How Inteldo answers a question
When you ask a question, the Inteldo orchestrator routes it to the specialists that own the relevant data. The Revenue Analyst reads Stripe, the Traffic Analyst reads GA4 and Search Console, the Product Analyst reads PostHog, and the SEO Analyst covers rankings and page performance.
The agents investigate in parallel and report back in a real-time chat workspace. You watch the investigation unfold, and the final report links every claim to the data it came from, so the answer is checkable rather than a black box.
Conversational analytics tools compared to dashboards
Dashboards answer the questions someone predicted months ago. Conversational analytics answers the question you have right now. The practical difference shows up in incident response and weekly planning, where the question changes every time and rebuilding a dashboard per question is not realistic.
The two are complements, not rivals. Teams typically keep dashboards for routine monitoring and use conversational analytics for investigation, root-cause work and one-off questions from leadership.