Index
A case-based quote may look more expensive than a unit-based quote while offering better terms. Extracting prices without their commercial units produces comparisons that cannot support purchasing decisions.
The design to commission
Require identification of items, units, pack contents and stated supplier conditions. Similar descriptions do not prove technical equivalence, and AI must not invent missing conversion factors. Keep source documents inspectable alongside normalized tables. Define conversions authorized by master data and those requiring buyer review. Before implementing AI, test structured quotation forms; they may reduce ambiguity at intake. Assistance becomes useful when teams receive varied formats and spend time organizing information. Separate preliminary comparison from supplier selection and purchase approval. Delivery terms, stated taxes and validity periods should retain context without the system issuing tax interpretations. Suppliers should demonstrate uncertain item matching and propagation of human corrections into validated master data. Measure success by a reviewable comparison rather than the number of prices extracted, because a confident but incorrectly normalized value can misdirect purchasing.
Supplier criteria
- Connect prices to units and packaging composition.
- Trace conversions to authorized master-data rules.
- Have accountable buyers confirm specification equivalence.
Acceptance with an exception
For hypothetical acceptance, one quote lists a case without pack quantity and another lists individual units. The table should flag incomplete comparison rather than assume standard packaging to select the lowest price.
Reference for assessing scope
Prepare your project with Quantum9
Bring Quantum9 anonymized quotations and current item-equivalence rules. We assess structured intake, assisted extraction and the review required before a commercial decision is made.