Satie.

The problem

Every large enterprise running an agentic transformation has committed to it — but the reasoning engine they need to execute it doesn't exist. Inference tools observe activity (calendar, comms, work apps). Engagement surveys collect sentiment. Neither reasons across strategic intent and operational capability. The result: the evidence underneath strategic decisions is fiction or it is missing entirely.

Leaders commit to operating-model changes, agentic adoption plans, and reorganizations based on opinions and slide decks, then discover during execution that the analytical substrate was never actually built. Primary research (real conversations with the people doing the work) doesn't scale — months of consultant fieldwork covers a fraction of the org and is stale by the time it lands.

The solution

Satie is the reasoning layer: strategic intent in, executable organizational intelligence out. The system ingests strategic direction documents (CHRO memo, restructure plan, OKR framework) and organizational context (roles, skills via TechWolf, reporting structure), then runs AI-facilitated structured interviews with SMEs at scale — capturing the qualitative substrate that surveys can't reach and consultants can't deliver at the speed transformation actually requires.

Output is evidence-mapped, exec-ready intelligence: which roles are aligned to strategy, where the skill gaps actually sit, which org units have the capability to absorb agentic work and which don't.

How it works

Four stages: (1) Strategic Context Ingestion (~10 min, admin-driven) — paste/upload the strategic doc and the org context doc; structured extraction runs on Opus. (2) Conversational Intelligence — the Interviewer agent (Sonnet 4.6) runs adaptive interviews with SMEs, holding multi-turn context and adapting to the conversation. (3) Reasoning — synthesis across the interview corpus, mapped against strategic intent and skills data. (4) Output — exec briefings, role-level findings, evidence map.

Seven primary interfaces surface the four layers: Strategic Intent Tab (admin), Org Context Tab, Interview Console, SME Dashboard, Synthesis View, Findings Brief, Exec Summary. Three-tier model strategy — each tier chosen for fitness to its specific job, not as a single-model default. Working v5 prototype is a ~5,500-line JSX Claude Artifact demonstrating all four capabilities end-to-end.

Who it's for

Three distinct personas, all three must receive value or the platform fails (multi-sided platform by design):

Primary (paid tier): HR Center of Excellence Professional — Skills, L&D, Workforce Planning, Talent Acquisition, M&A specialists at large enterprises running the transformation. They own the workflow and benefit from primary research at scale.

Secondary: SMEs across the organization — they participate in the AI-facilitated interviews and need the experience to feel valuable, respectful, and worth their time.

Tertiary: Executive Sponsor (CHRO, Chief Transformation Officer) — the budget holder, consuming the synthesized output. They need exec-grade intelligence that holds up to board scrutiny.

Why it matters

The market is shaped by a hard reality: every large enterprise has committed to agentic transformation, none has the reasoning substrate to execute it well. Surveys, inference tools, and consultant fieldwork each cover a slice; none synthesizes strategy + capability + sentiment into executable intelligence.

Satie's positioning bets that the reasoning layer above the workforce intelligence stack is the strategic-tier wedge — and that the same primary-research substrate that powers transformation planning today becomes the foundation for ongoing workforce intelligence tomorrow. Blended entry-market growth at 18–24% CAGR across the four converging subsegments validates the timing.

At a glance

Project

Satie

Built by

Cole Monroe

One-liner

Strategic alignment engine for agentic organizational transformation — the AI reasoning layer above the workforce intelligence stack.