Overview
Overview
Production planning teams
Vehicle allocation / order management teams
Operations and supply chain planners
Plant and logistics coordinators
Consolidates daily order and vehicle-allocation data from Excel into a centralized Postgres database
Matches orders to vehicles using deterministic, rule-based logic
Replays and simulates allocation scenarios to make outcomes auditable and explainable
Maintains persistent, context-aware chat for ongoing planning conversations
Analyzes documents and images relevant to orders and allocation exceptions
Provides read-only SQL and rule access for transparent querying of planning data
Prepares previewable, impact-scoped draft actions rather than deciding autonomously
Manages exceptions through a human-approved workflow, applying changes only after approval with a full audit trail
Consolidates data from Excel workbooks into a centralized Postgres database
Built with the Claude Agent SDK and MCP (Model Context Protocol) tools for the agent layer
Provides read-only SQL access for querying allocation rules and planning data
Supports document and image ingestion for order-related exception review
Can be embedded into existing planning dashboards or operations portals
Agent layer built with the Claude Agent SDK and MCP tools, rather than free-form autonomous decision-making
Deterministic, rule-based matching engine drives order-to-vehicle allocation
Replay/simulation capability makes every allocation outcome auditable and reproducible
Strictly human-in-the-loop: the agent prepares previewable draft actions and applies changes only after explicit human approval
Full audit trail recorded for every approved action
Available for cloud, on-premise, or hybrid deployment
Reduces manual reconciliation of order and vehicle-allocation data from hours to minutes
Improves allocation accuracy through deterministic, rule-based matching
Increases auditability of planning decisions via replay and simulation
Ensures no allocation change is applied without human approval
Accelerates exception handling with document/image-aware draft resolutions
Enhances planning transparency through read-only SQL and rule access for all stakeholders
Cuts the risk of manual data-entry errors from spreadsheet-based coordination
Automotive Manufacturing – primary use case, daily order-to-vehicle allocation planning
Industrial Manufacturing – production and inventory allocation planning
Logistics & Supply Chain – order fulfillment and resource matching
Heavy Equipment & Machinery – build-to-order allocation planning
Purpose-Built AI Agents Powering the Future of Work