Kbot Workforce: Autonomous Team Governance, AI-Helper & KPI Measurement
Kbot Workforce connects daily scheduler planning, step-by-step AI-Helper execution blueprints, and evidence-verified KPI measurement into one automated engineering and sales operating system.
Two-Tier Workforce Governance: Main Pillar (Set 1) & 2nd Pillar (Set 2)
How Kbot Workforce calculates and measures performance across engineering and sales: The 1st Pillar (Main Pillar in KPI โ Set 1) shares its fixed 100% weight across core outcome dimensions. The 2nd Pillar in KPI (Set 2) is defined dynamically by Admin via the AI-Helper based on today's active Requests (To-Do), where Admin sets any task duration (1~8h max) and AI automatically balances the rest of the hours (summing to 8.0h total) and weights/points (summing to 100%) to feed and validate the 1st Pillar.
๐ 1st Pillar: R&D Main Outcomes (Set 1 in KPI) 100% Fixed Shared Weight
๐ค R&D AI-Helper Sample Console โ Set How to Measure 2nd Pillar
What Kbot Workforce Solves
Traditional team management relies on manual check-ins, subjective estimates, and disconnected issue trackers. Kbot Workforce transforms team operations into a zero-meeting, self-evident execution pipeline:
- Evidence-Backed Delivery: Tasks score only when backed by signed Git commits, green CI runs, or customer message transactions.
- Strict 8.0h Daily Sizing & AI Allocation: Admin sets time budgeting (1~8h max per request) and the AI automatically calculates and allocates the rest of the hours (summing to 8.0h total) and proportional points (100 pts per day) across any number of requests (1 to any), eliminating arbitrary overages and ghost hours.
- Lean Dual-Track Acceptance: Track A deterministic probes execute in under 5 seconds with zero token expense, followed by brief human usability checks.
- Automated Reconciler: The AI-Helper continually monitors production logs, Git SHA diffs, and database events to auto-credit completed deliverables.