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SkyNet uses AI decisioning to prepare commercially checked air quotes
Added 2026-10-14 · Reviewed 2026-10-15 · SkyNet
Read the source ↓What the company did
Aircon reports SkyNet introducing an AI decision layer alongside manual air-freight quoting. It evaluates carrier options, validates surcharges and applies margin floors and customer pricing rules before quotes reach customers, giving pricing staff time to compare agent outputs during adoption.
How it went
The case says agent-generated quotes reached 58% of the total by January and manual work fell from 50 to 21 hours monthly with similar output. Its approximately 3.3-hour full-automation scenario is theoretical, not achieved performance; the provider supplies no public evaluation protocol.
Worth knowing
- Bulk tender and RFQ expansion belonged to the next phase rather than the reported deployment.
- For your desk: Compare the selected carrier, surcharge completeness and margin against the customer’s service needs. Separate quoted pipeline from booked revenue when assessing the result.
Sources & provenance
SkyNet Case Study: Breaking the Quoting Ceiling ↗
Aircon · Published 2026-04-06 · Reviewed 2026-10-15
“Aircon was introduced as an embedded decision layer”
Supporting evidence and review
Human review required
- Practical review advice: confirm available capacity, transit feasibility and charge validity.
- Review margin floors and customer agreements before approving a commitment.
Evidence & limitations
- Provider-published named customer case; no independent quotation evaluation.
- Optimization and commercial validation are provider claims with no public test protocol.
- Projected full-automation hours and future bulk-RFQ expansion are not deployed outcomes.