We build AI that extracts vendor and tax-form data from your PDFs, cross-checks it against IRS TIN Matching and your vendor master, and flags every mismatch — cited to the source, or an honest “not found.” Built to run alongside your existing AP stack, including Esker — not replace it.
Your core AP automation handles the standard flow well. This is for the specific, recurring exceptions that still land in someone’s inbox.
The situation. Your AP team is heading into 1099 season with hundreds of vendor payments to reconcile against W-9s on file — scanned forms, PDFs, and whatever made it into the vendor master over the years.
The pain. Missing or mismatched TINs mean IRS B-notices, backup withholding and penalties — and finding them today means someone reading every W-9 by hand against every payment record.
What we’d build. Extract TIN, legal name and address from every W-9 and payment record, cross-check against IRS TIN Matching, and flag every mismatch or missing form — cited to the source document.
The goal. Exceptions surfaced weeks before the filing deadline, not after a B-notice arrives. Proposed pilot: 2–4 weeks on a sample of your own vendor files.
The situation. Your vendor master has grown for years across onboarding, mergers and one-off suppliers — duplicates, stale addresses and inconsistent TINs pile up quietly.
The pain. Bad vendor data causes misdirected payments, failed 1099 filings and audit findings — and cleaning it by hand doesn’t scale past a few hundred records.
What we’d build. Extract and normalize vendor records from your source documents, flag likely duplicates and TIN/name mismatches, and cite exactly where each conflict comes from.
The goal. A cleaner vendor master before it causes a payment or filing error — not after. Proposed pilot: 2–4 weeks on your own vendor master export.
The situation. Esker (or your core AP automation) handles the standard invoice-to-PO flow well — but edge cases still land in someone’s inbox: unusual formats, multi-entity vendors, ad-hoc compliance checks.
The pain. Every AP team has a long tail of exceptions that don’t fit the standard automated path — currently a manual, ad-hoc process running alongside the “real” system.
What we’d build. A targeted AI layer for your specific long-tail exceptions — extraction, validation and flagging — that plugs in next to your existing platform.
The goal. The 90% your platform already automates stays untouched; the remaining 10% gets the same rigor instead of falling back to manual work.
We layer on top of your existing AP automation and ERP. Nothing to migrate, no new system of record.
We build the custom layer for your specific edge cases — 1099s, vendor validation, whatever doesn’t fit the standard path — and it runs next to Esker, not instead of it.
A human reviews and approves every exception. We surface cited evidence — your team decides.
Every flag points to the source document and field it came from. If it isn’t there, it says so.
Each legal entity’s vendor and tax data is walled off from every other.
OCR turns scanned W-9s, 1099s and PDFs into structured, validated data.
Your vendor and tax records are never used to train shared models.
In 2–4 weeks we run it on a sample of your own vendor files and 1099/W-9 records, measure accuracy, and show you exactly what it would have caught — before any commitment.
Unlike our contract-Q&A engine below (which is live today), we haven’t built the 1099/vendor-validation pipeline yet. Here is exactly how we’d build it.
Connect your AP inbox or DMS, or upload manually: W-9s, 1099s, invoices, vendor records — PDFs, scans, or exports.
OCR + LLM extraction pulls TIN, legal name, address and amount into structured fields — not just searchable text.
Cross-check against IRS TIN Matching and your vendor master. Every mismatch, missing form or duplicate is flagged and cited to its source.
Exceptions land in a review queue for your team. Nothing files or pays itself — a human approves every resolution.
Steps 1, 2 and 4 above already run in production on contracts — ingest, OCR, structured citation, and a refusal guardrail when the answer isn’t in the documents. Step 3 (external validation against IRS/vendor-master) is the new piece we’d build for AP.
In progress — report available under NDA once complete.
Deploy in your region — US or EU.
Each legal entity’s vendor and tax data is walled off from every other.
TINs and other sensitive identifiers are handled as regulated data, not plain text.
Role-based access plus a tamper-evident audit trail.
Your vendor and tax records are never used to train shared models.
No. It’s a targeted layer for the specific gaps your core platform doesn’t cover — 1099 reconciliation, vendor data validation, and similar edge cases — designed to run alongside Esker, not instead of it.
Against the IRS TIN Matching Program and your own vendor master, where available. Every mismatch is flagged with the source document and field it came from, for your team to confirm.
TINs are treated as regulated PII: per-entity isolation, your choice of data residency, role-based access, a full audit trail, and no training on your data.
The 1099/vendor-validation pipeline described on this page is a proposed build, scoped as a paid pilot on your own data. The underlying engine — OCR, extraction, citation, guardrails — already runs live; you can try it on contracts today.
Handled with OCR, same as scanned contracts — turned into structured, validated data alongside anything already digital.
Tell us about your 1099/vendor-validation gap and what’s currently manual. We’ll show the live engine and scope a paid pilot on a sample of your own data.