For early-stage startup teams, Trace is a workflow orchestration platform that routes tasks between human teams and AI agents, coordinating handoffs so work moves without manual triage.

Presence & Market Position

19
SOV ScoreSOV Score — earned, engagement-weighted share of voice across Adam's curated panel of GTM voices, scored against the market. Earned only: a brand's own posts do not count. Not a quality rating, endorsement, or paid placement.

#66 of 78
AI-Native GTM Challengers

Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →

Trace is positioning itself as the context and orchestration layer for companies running AI agents alongside human teams. Its broader conversation footprint remains early, so the current position is defined mainly by product releases and customer use cases. The product connects workplace systems, builds a graph of people, projects, clients, and tasks, and turns plain-language processes into workflows with agent steps, human assignments, and approval gates. Recent company writing emphasizes evaluation, governance, and explainable handoffs as the operating requirements for moving agent experiments into production.

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Customers

YAYA, Trag, GodmodeHQ, &Volume, GreenRepublic

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Business Profile

Founded in 2025, Trace is an independent London-based software company with five employees and $3M in funding. The business emerged from Y Combinator’s Summer 2025 batch around the idea that workplace agents need organizational context before they can handle durable operational work. Its funding supports deeper integrations, a wider agent ecosystem, and movement from single workflows into multi-team deployments. Trace is currently focused on back-office processes such as client onboarding, document handling, account management, HR screening, and sales operations.

Founded
2025
Employees
5
Funding
$3M
Status
Independent
Scale stage
Startup
Type
Orchestration
GTM categories
Data & Intelligence

Agent Readiness

13F
Agent ReadinessAgent Readiness — how easily an AI agent can build on this product: documented API, MCP server, CLI and SDK surfaces plus the depth of the docs behind them. Scored 0-100 and graded A-F.
APIMCPSDKCLI

Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →

Trace’s AI strategy centers on a knowledge graph that supplies agents with company context at execution time. Teams describe processes in plain language; Trace converts them into workflows where agent tasks run automatically, human tasks pause for the right assignee, and approval gates protect irreversible actions. No public API, MCP, SDK, or CLI is available on file. The company has publicly identified a third-party SDK as part of its build-out.

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