We ingest data from the systems your team lives in (CRM, email, calls, meetings, tickets) so every signal needed for productivity intelligence is available end-to-end.
Instrumentation turns raw tool activity into clean, auditable signals—who did what, when, and in what context. These atomic signals become the input to every model and insight. Building blocks of work are captured—activities, messages, interactions, artifacts, and outcomes—so intelligence is grounded in evidence, not guesswork.
Instrumentation turns raw tool activity into clean, auditable signals—who did what, when, and in what context. These atomic signals become the input to every model and insight. Building blocks of work are captured—activities, messages, interactions, artifacts, and outcomes—so intelligence is grounded in evidence, not guesswork.
Productivity models define what “good” looks like for a role: the mindsets, skills, and goals that matter—plus the rules and AI models used to evaluate them. We translate signals into Mindsets, Skills, and Goals (MGSA) so performance becomes observable and coachable—grounded in evidence and measured over time.
This is where the system becomes operational. We detect risk and upside, explain the “why” with supporting signals, and prescribe next steps—so teams move from reactive management to proactive coaching and outcomes.
