Code alone does not tell the full story of your operations.
We expanded our neutral AI layer to evaluate the entire business. Our system now connects directly across your sales pipelines, project boards, and code repositories. It tells leadership exactly what the team is building, what deals are moving, and where things are stuck. 📈
Reading the whole organization
We officially renamed the core product to AI Manager. The previous identity narrowed the focus strictly to engineering. Many founders already connect CRM platforms, support systems, and daily communication channels. The updated system acknowledges this reality. It drops the engineering-only constraints and evaluates health across all active departments.
When you ask for a team check-in, the agent reviews every connected pillar. It looks at GitHub commits, Jira tickets, and HubSpot deal stages simultaneously. You get a single clear measure of overall health from 0 to 100 instead of a siloed engineering metric.
Focused setup and immediate reads
Supporting a wider scope required a completely new onboarding sequence. We replaced the old repository-only flow with a multi-connector configuration design. âš¡
You choose a primary direction like Engineering, Sales, or Projects. You then connect your specific platforms. The system guides you to configure exact data boundaries before running its first evaluation. Your initial 30-day performance read generates within minutes of signing up. It builds this report using only the platforms you explicitly authorized.
Tighter data synchronization
The underlying synchronization engine now handles complex multi-tool setups effortlessly. Configuration rules apply instantaneously at the moment of connection.
This precise scoping means the AI reads only what you approve. If a specific department has no connected tools, the prompt builder drops those questions entirely. The agent never invents metrics for disconnected platforms. It relies strictly on hard data from your active ecosystem to show you what is real. 🚀