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Crossary proposes every source-to-target mapping with the verbatim source quote it's based on and a self-rated confidence and abstains instead of guessing when nothing fits. Excel, JSON, XML, PDF, CSV. Export a reviewed workbook that round-trips.

Website, pricing, platforms and company facts side by side.
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| Website | crossary.com | codegres.org |
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In their own words, as submitted to SaaSHub.


Crossary helps integration and migration teams turn source and target specification documents into reviewed, implementation-ready data-mapping workbooks. Upload both sides' specs — Excel, PDF, CSV, JSON, XML, XSD, SQL, or YAML — and Crossary extracts a field inventory from each, then proposes a...
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As answered by people managing Crossary and Codegres.org.
Crossary's answer
Crossary doesn't just propose a mapping — it shows its work. Every row comes with the exact verbatim source quote it's based on, the reasoning and assumptions behind it, and a confidence score, so nothing is taken on faith. Where most tools would guess to fill a gap, Crossary abstains and flags it instead — "a wrong mapping is worse than an honest gap" is the core design principle. It also works from specs, not production data (so there's usually no need to upload real records or PII), and its export isn't a locked app view — it's a signed .xlsx you can edit anywhere and re-import without losing a single reviewer note.
Crossary's answer
Most mapping tools either require you to build the sheet by hand or hand you an AI guess with no way to verify it. Crossary sits in between: it proposes mappings backed by evidence and reasoning you can actually audit, validates the structure deterministically (zero AI cost), and never overwrites your edits on re-import — matched changes apply, moved rows are skipped, and notes become tracked questions. Reviewing, validating, exporting, and round-trip re-import are free on every plan, so you only pay for the AI runs themselves, not for checking the work.
Crossary's answer
Crossary is built for the people who hand-build mapping sheets that someone else implements: integration and interface engineers mapping heterogeneous specs (PDF, XML, EDI-style guides, Excel) to a target schema; implementation and onboarding consultants turning a client's messy spec into a reviewed workbook on day one instead of week three; data and migration engineers building the field inventory before any records move; and EDI/interface analysts who need evidence-backed rows that hold up to scrutiny later.
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