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Spot Pricing Engine for Freight Quotes

In-depth look at how we combined AI extraction, rate logic, and guardrails to accelerate freight quote turnaround.

Delivered last month for a UK freight forwarder (commercial team of 6, ~100 inbound quote requests/month).

Spot Pricing Engine for Freight Quotes

The freight market’s shift toward spot pricing means rates move fast — speed is now the competitive edge. Previously, operators re-keyed inbound emails into templates, hunted rates across portals and spreadsheets, calculated margin, and drafted responses by hand. Quotes stalled in inboxes (revenue leakage) and throughput was capped by manual effort.

In four weeks we deployed an Instant Revenue Engine that turns inbound quote emails into a ready-to-send draft in seconds, with a human review gate before sending. Time to first draft: minutes → seconds. Same team, more quotes issued. Faster responses lifted win rate on spot opportunities.

Time to first draft: minutes → seconds
Higher quote throughput with the same team
Faster responses improved conversion on spot opportunities

What we built

  • Read inbound quote requests from email (unstructured text, PDFs, messy formatting).
  • Extract shipment fields with an LLM (origin, destination, incoterms, dimensions, weight, commodity, readiness date, service level).
  • Pull matching rates, apply margin rules, and draft the quote email for operator approval.

Operator-safe guardrails

  • Confidence scoring routes low-certainty extractions to “Needs input.”
  • Mandatory fields (origin/destination, mode, weight/volume) before a final draft is produced.
  • Rate traceability links each quoted rate back to its source (sheet, API call, portal scrape).
  • Lane-level margin rules with minimum thresholds.

What this unlocks next

  • Auto-follow-ups at +2h / +24h if no reply
  • Lane intelligence for conversion and churn patterns
  • Dynamic pricing that adjusts markups by demand and customer tier
  • CRM/TMS integration for quote-to-book tracking

Key design choice

Kept a human approval gate so the commercial team stays in control while automation does the heavy lifting.

Why this isn’t “just automation”

  • Faster quotes → more quotes issued
  • More quotes issued → more wins
  • More wins → measurable gross profit uplift

Revenue impact

Even with conservative assumptions, a 5 percentage point win-rate lift on £300 margin shipments yields ~£18,000 additional annual gross profit.

At a glance

  • Inbound emails parsed to structured shipment details.
  • Rate engine applies lane logic and margin rules.
  • Operator reviews the generated quote before sending.
  • Audit logging and CRM/TMS updates for traceability.

Diagrams

Manual quote workflow (before)
Automated quote workflow (after)

See what this could look like for your business

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