Trace

Trace is an operational layer designed to act as the central nervous system for modern teams, enabling context-aware automation that bridges AI agents and human judgment across departments. Instead of being a generic workflow tool, Trace understands how a company actually operates—its internal processes, document flows, approval chains, and cross-functional handoffs—by ingesting real business data and learning from ongoing activities. The platform provides a unified interface where teams can define, monitor, and refine automated sequences that integrate with existing tools like CRMs, document repositories, and communication platforms. For example, when a new client onboarding is triggered, Trace automatically creates a workflow that spans sales, operations, finance, and compliance. It extracts contract terms from uploaded PDFs (such as Acme_MSA.pdf), identifies key values like contract amount ($85,000), term length (12 months), auto-renewal clauses, and then applies business rules: if the value exceeds a threshold (e.g., $50K), the system routes the contract to the finance team for approval with a high-priority flag. Simultaneously, it assigns tasks to specific users (@sarah.chen) and updates the status of each step in real time—from task completion notifications to pending reviews. Beyond onboarding, Trace handles recurring operations like workflow review, agent task delegation, and activity logging. Its "Context Engine" captures the nuance of each department’s requirements: sales might need quick contract extraction, finance requires compliance checks, and operations wants visibility into all moving parts. The platform not only orchestrates AI agents (like those that extract data, validate conditions, or generate summaries) but also escalates to humans when judgment i