Freight RFQ to Quote
From shipment request to quoted price with rate lookup, carrier coordination and TMS integration. This is a reference workflow pattern — NorthFlow starts with the workflow that matters inside your business.
Current flow
A freight forwarder receives an RFQ via email or portal with shipment details: origin, destination, weight, dimensions, commodity and service requirements. A team member manually enters the data into the TMS, looks up rates across multiple carriers or rate sheets, calculates margin, prepares a quote, and sends it back. Response time depends on team capacity, and RFQs can slip through when volume spikes.
RFQs arrive as unstructured emails or PDFs. Rate data lives in carrier portals, spreadsheets and internal rate sheets with no unified lookup. Manual data entry introduces errors. Carrier selection requires weighing price, transit time and service level tradeoffs that depend on context.
Target flow
An AI-enabled workflow that extracts shipment details from RFQs, looks up rates across configured carriers and rate sheets, applies margin rules, generates a quote, and proposes it for operations team approval before customer response and TMS entry.
AI reads the RFQ from email or portal, extracts origin, destination, weight, dimensions, commodity and service requirements, and structures the data.
AI queries configured carrier APIs, rate sheets and contracted rates, filters by service level, and returns options with transit time and price.
AI applies margin rules, selects optimal carrier option based on configured logic, and prepares a draft quote with all charges and transit time.
Operations team reviews the quote, can modify carrier selection or margin, approves the response, and the system sends the quote and writes to TMS.
Existing systems
The TMS, carrier portals, rate sheets and email system remain in place. NorthFlow adds a workflow layer that connects these systems without replacing commercial decisions.
NorthFlow layer
AI document extraction, rate lookup API orchestration, margin calculation, quote generation, and TMS write API. Carrier selection and commercial decisions remain with the operations team.
Production controls
AI can read RFQs and look up rates but cannot send quotes or write to TMS without approval. All quotes are reviewed by the operations team before customer response. Team can override carrier selection or margin. Every action is logged for audit. Unusual requirements or pricing exceptions escalate to a person.
AI Operations Agent
This is an interactive demonstration using synthetic business data, not a completed client deployment.
- What this demonstrates
- An AI operations system that ingests updates, identifies blockers, proposes tasks and requires human approval before execution.
- Which part of the workflow it maps to
- The operational coordination, task routing and approval workflow patterns applicable to freight operations.
- What would change in production
- The demo uses synthetic project data. In production, the AI would connect to your TMS, carrier APIs and operational systems with proper authentication and rate limits.
Evaluate before building
Custom engineering creates value when the workflow is important, repeatable, and has a clear return on investment. Consider alternatives when:
- RFQ volume is too low to justify automation
- Carrier rate APIs are not available or reliable
- Rate sheets change too frequently for structured lookup
- Commercial decision logic is too context-dependent
- Existing TMS already handles the workflow adequately
If off-the-shelf software, spreadsheets, or existing tools can handle the workflow adequately, start there. Build custom software when the gap between what exists and what you need is material and measurable.
Who should build this
Freight forwarders, 3PLs and logistics businesses with high RFQ volume, carrier API access, and a clear need to improve response time and operational efficiency.