Trace

What do they actually do

Trace is a web-based workspace for automating multi-step work across a company’s existing tools. Teams connect apps like Slack, Jira, and Notion; Trace builds a context index from docs, activity, and people data; and it breaks jobs into tasks that are routed either to a human or an AI agent, with humans kept in the loop for reviews and approvals (Trace site, YC profile). A public demo and free signup are available at trace.so.

A typical flow: connect tools, create a workflow from a prompt or template (for example “onboard a new client”), let Trace decompose it into tasks, and have Trace assign tasks to a person or an AI component while syncing permissions and logging each step. Users can review outputs, rerun failed steps, and rely on audit trails and rerun controls to keep work traceable (Trace site).

The product is early but live, with a focus on mid-sized teams. At launch, the company reported more than 30 companies using Trace and showed initial traction through a public demo, Product Hunt, and early paid signups. The YC page lists a 5‑person team in the Summer 2025 batch (YC profile, Product Hunt).

Who are their target customer(s)

• Operations / Workflow owners: They run cross-functional processes across multiple tools and teams, leading to manual handoffs, missed steps, and slow completion. They need integrations, automation, and an audit trail to reduce coordination work (Trace — Features).
• Customer Success / Onboarding managers: Client onboarding spans Slack, Notion, Jira, and multiple people; status gets lost and context is re-created, delaying go-live and risking churn. They want templates and standardized task breakdowns to track progress (Trace — Features).
• Product managers / Engineering leads: Releases, bug triage, and incidents involve fragmented information and partial handoffs, causing context loss and slow follow-through. They need jobs broken into tasks with context attached and routed to the right person or AI (YC profile).
• People Ops / HR teams: Employee onboarding/offboarding touches many systems and approvals, creating delays and security mistakes. They need a context engine and permission sync to automate multi-system flows safely (Trace — Features).
• Finance / Legal / Compliance teams: Approvals, contract reviews, and audits are slowed by ad hoc handoffs and poor traceability, increasing risk and delaying payments or deals. They need audit logs, rerun controls, and workspace governance to make processes reliable (Trace — Features).

How would they acquire their first 10, 50, and 100 customers

• First 10: Convert traffic from the public demo, free signup, YC network, and Product Hunt into hands-on pilots where founders help set up real workflows and custom templates for early teams (Trace demo, YC profile, Product Hunt).
• First 50: Publish vertical templates and walkthroughs (e.g., customer onboarding, HR onboarding), run live demos/webinars hooking into Slack/Jira/Notion, and amplify early wins as short case studies to attract similar teams (Trace — Features & integrations).
• First 100: Operationalize a repeatable motion (self-serve signup → guided pilot → paid) with light CS/sales support, standard onboarding playbooks, and hardened permissions/audit to serve larger teams; add integration/template partners to drive bundled implementations (Trace — Features, YC profile).

What is the rough total addressable market

Top-down context:

Trace participates in workflow/workforce automation, RPA, and emerging AI agent orchestration. 2025 market sizes cited by analysts are roughly: workflow automation ~$23.8B, RPA ~$6.3B, and AI agents ~$7.6B; combined near-term ≈ ~$37.7B, with the categories projected to exceed ~$100B by 2030 (Mordor workflow, Mordor RPA, Grand View — AI agents, MarketsandMarkets — AI agents).

Bottom-up calculation:

As an initial reachable segment, assume 150,000 mid-market teams globally that run cross-tool workflows (Ops, CS, HR, Product) and would adopt a context-aware human+AI workflow system; at an average annual contract value of $10,000–$25,000, this implies ~$1.5–$3.75B in bottom-up opportunity for Trace’s current focus. This can expand with enterprise features and broader agent orchestration coverage.

Assumptions:

• Targetable mid-market companies with multi-tool workflows ≈ 150k globally across key functions
• Product ACV in early/mid-market ranges $10k–$25k per account
• Estimate excludes very small teams and assumes modest penetration within eligible companies

Who are some of their notable competitors

• Workato: Enterprise iPaaS and orchestration with strong security, governance, and approvals for complex cross-system processes; overlaps on multi-step automation and human approvals but is oriented to large IT/enterprise programs (Workato, AI agent & approvals).
• Make (Integromat): Visual, no-code automation with a large connector library and human-in-the-loop/AI support; overlaps on orchestration and templates but is a general-purpose iPaaS rather than a company context index with BYOA governance (Make product, HITL enterprise).
• Tray (Tray.ai): Low-code/enterprise automation marketed as AI-ready with agent builders and governance; overlaps on agentic orchestration for IT and developer teams at scale (Tray.ai).
• Tonkean: Operations orchestration focused on human-in-the-loop approvals, conversational intake, and process templates for shared services; similar human+AI handoffs, with a people-centric orientation (Tonkean platform, Enterprise Copilot).
• Zapier: Broad, self-serve automation with extensive templates and simple approval workflows; easy for one-off automations but not centered on company context indexes, BYOA agent orchestration, or enterprise governance (Zapier templates, Approval workflows).