RADICL provides an AI‑native platform that continuously captures real‑time work patterns from calendars and workflow tools to generate live team health KPIs. It detects gaps in clarity, trust, and execution, offering actionable insights and capability mapping to improve cross‑functional collaboration for mid‑size to large enterprises.
Funding
Funding not disclosed
Founders
Product
Problem
Organizations struggle to identify and resolve friction within teams, such as unclear roles, low trust, and execution gaps, because existing tools focus on individual metrics or rely on static surveys that provide delayed, incomplete insights.
Solution
RADICL offers an AI‑native platform that continuously captures real‑time work patterns by integrating with calendars and workflow applications, delivering live data‑driven insights into team performance. The system surfaces breakdowns in clarity, trust, and execution, turning personal observations into actionable, enterprise‑wide metrics. By focusing on collective productivity, RADICL helps teams unlock hidden strengths, align capabilities, and build stronger connections without disrupting existing processes. Insights are presented as continuous KPIs for team health, enabling leaders to intervene promptly and improve collaboration outcomes.
Target Audience
Primary customers are mid‑size to large enterprises seeking to improve cross‑functional collaboration, as well as HR and people‑operations teams responsible for team effectiveness and organizational performance.
Features
- Seamless integration with calendar and workflow tools to automatically record how work actually happens
- AI‑powered analytics that detect real‑time gaps in clarity, trust, and execution across teams
- Live team performance dashboards that translate personal insights into enterprise‑level KPIs
- Capability mapping that matches skills and work styles to optimal roles and collaborations
- Trust and connection metrics that surface chemistry breakdowns and suggest interventions
- Design‑focused UI that presents actionable recommendations without requiring manual surveys