Evidence before conclusions
Important analysis retains product, metric, time window, source, and freshness context so operators can inspect why an answer was produced.
Dashloom is an open-source AI product intelligence platform. It connects acquisition, search, revenue, product, and infrastructure signals so independent builders and small teams can understand change, act, and build a repeatable operating rhythm.
A digital product lives across analytics, search consoles, billing systems, repositories, and cloud infrastructure. Each tool explains a fragment, but cross-system questions remain hard: where did revenue growth come from, did search growth produce paying users, and did a release affect both errors and conversion?
Dashloom builds a unified, product-aware data layer and lets specialized agents work on that evidence. It does not replace source systems; it turns their facts into next moves that can be inspected, discussed, and executed.
Important analysis retains product, metric, time window, source, and freshness context so operators can inspect why an answer was produced.
Dashloom is not trying to create more dashboards. It helps teams identify change, choose a next move, and measure what happened afterward.
The core product is MIT licensed, self-hostable, and compatible with OpenAI-style model APIs. Cloud is a lower-operations path, not a prerequisite for control.
Agents operate on bounded evidence and permissions. Imported text cannot rewrite system rules, and correlation is not presented as causation.
MIT licensed, operated and customized by you with your own models and infrastructure.
Use the complete workflow without deployment for a small product portfolio.
Add capacity, automation, collaboration, alerts, and agency workflows.
Use the GitHub repository for feature ideas and community discussion. Email us for billing, privacy, or Dashloom Cloud support. Report vulnerabilities privately through the repository Security Policy rather than disclosing them publicly.