Reporting layer for AI operations teams

The moment someone realizes they have this problem is when their VP asks for a quarterly review of the AI agent's performance and they're staring at a locked-down dashboard with three bar charts and no drill-down. They can export a CSV, but turning that into something defensible takes an afternoon in Excel or a request to the data team.

This gap persists because the AI ops vendors — AgentVoice, Aisera, Aissist and their peers — are primarily incentivized to sell on capability, not on reporting depth. Their buyers are operations leaders or IT buyers who care about deployment; it's often a different person (a team lead, a program manager, an analyst) who needs the reports, and that person has no voice in the purchase decision. So the vendor ships a minimal dashboard, marks it 'done', and moves on. Fixing it properly would require them to rebuild a meaningful chunk of their product for a user who doesn't write the check.

What these tools get wrong specifically: the dashboard stays the same regardless of which tables or flows a team actually uses; there's no way to build year-over-year comparisons; reports can't be scheduled and emailed; per-agent resolution statistics aren't exposed; and shared reports load slowly enough that stakeholders stop opening them. Exporting to PowerBI or Tableau is technically possible but requires enough setup that most teams never get there.

This is a business and not a feature because the need recurs on a predictable cadence — monthly ops reviews, quarterly business reviews, annual budget justifications — and each cycle the same person is rebuilding the same export-and-format ritual. The cost is real: a mid-size operations team losing three to five hours per reporting cycle, plus the softer cost of presenting weak visuals to leadership and having the AI investment questioned. Any tool that eliminates that ritual and produces board-ready output automatically has an obvious, recurring value proposition.

What to build

Connect to the read APIs of major AI ops platforms (starting with Airtable and Aisera), pull agent performance, ticket resolution, and flow-level metrics into a reporting layer that lets ops managers build KPI-aligned views, schedule email delivery, and export PDF decks — without touching a BI tool.

Where to start

Start exclusively with Airtable, which has a public API, a massive installed base, and users who already complain loudly that its dashboard features aren't 'like Tableau' — build ten genuinely useful Airtable report templates and get traction there before touching any other integration.

The hard part

Every target platform has a different data model for 'agent performance', so normalizing metrics across even two vendors into a consistent schema requires painful, case-by-case API work — and if a vendor changes their schema, customer reports silently break.

How it makes money

Monthly subscription per workspace, tiered by number of connected data sources and report seats; free tier limited to two report templates and no scheduling.