By Quoveya editorial team · 21 May 2026 · 8 min read
A transparent, product-specific explanation of document processing, uncertainty, corrections, and the limits of AI-assisted offer comparison.
Quoveya uses AI to turn mixed offer documents into a reviewable comparison. It is decision support, not an automatic purchasing decision. The source documents remain the evidence, and users should verify decisive values before signing a contract.
Quoveya accepts the supported document and image formats shown in the upload interface. It extracts readable content, proposes providers, and structures fields such as prices, scope, exclusions, payment terms, delivery information, and warranties. Missing or uncertain information can then be reviewed before the comparison is generated.
The resulting table is useful because each provider is evaluated against the same set of fields. It does not make differently scoped offers equivalent by itself: exclusions, quantities, assumptions, and unclear wording still need human attention.
Quoveya does not guarantee error-free text recognition, perfect extraction, support for every possible file format, or a universally correct recommendation. Blurry images, handwriting, unusual tables, conflicting revisions, and domain-specific abbreviations can all produce uncertain or incorrect results.
Quoveya also does not independently confirm whether a vendor statement is true, whether a market price is reasonable, or whether a contract is legally suitable. Those judgments require source verification and, where appropriate, professional advice.
A useful comparison should distinguish four things: a value stated in a source, a value that is missing, an uncertain interpretation, and a recommendation derived from the reviewed information. Collapsing all four into one AI score would hide the reason for a result. Quoveya instead keeps review and correction in the workflow.
In the public synthetic case, an email amendment changes Northline Works’ payment term from 50% upfront to 30% upfront. The first extraction associates the amendment with the wrong provider because the screenshot uses a shortened sender name. The review step flags the provider assignment as uncertain. After the user assigns the evidence to Northline Works, the payment comparison updates while the original offer remains available as provenance.
This correction changes the commercial-risk assessment, but it does not automatically make Northline the best choice. Scope exclusions, warranty, delivery, and price still point in different directions.
Start with high-impact fields: total price, tax treatment, scope, exclusions, payment schedule, delivery date, and warranty. Open the cited source for any value that would materially affect the decision. Resolve uncertain provider assignments and check whether a revised email or attachment supersedes an earlier document. Finally, treat generated supplier questions as a review aid and edit them before sending.
Visible error and correction
A synthetic email from “N. Works Sales” changes offer NW-104 from 50% upfront to 30% upfront.
The shortened sender name is not confidently matched to Northline Works. The amendment initially appears as an unassigned source rather than silently overwriting a value.
The reviewer assigns the email to Northline Works and confirms that it supersedes only the payment schedule.
Northline changes from 50/40/10 to 30/50/20. Price, scope, delivery, and warranty remain unchanged. The commercial-risk assessment improves, but no automatic winner is declared.
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