Stop paying skilled operators to re-type PDFs.

Manual document work is a tax you pay in three currencies: time, errors, and morale. A clerk spends minutes per document keying fields, multiplied by hundreds or thousands of documents a month. Every entry is a chance for a transposed number or a missed expiration date, and the people doing it are usually overqualified for the task and quietly burning out on it.

The downstream cost is worse than the labor. A wrong amount on an invoice, a lapsed certificate of insurance that nobody flagged, a contract term that never made it into the system — these create real financial and compliance exposure. The paperwork bottleneck also slows everything that depends on it: billing, dispatch, onboarding, payment.

Each pipeline runs the same dependable stages: ingest the document, classify what it is, extract the fields, validate against your rules, and deliver the result via webhook to your ERP, CRM, accounting system, or storage. Confidence scores ride along with every extraction so the system knows what it's sure about and what it isn't.

High-confidence documents flow straight through to your system of record. Anything ambiguous lands in an exception queue where a person sees the original file and the extracted fields side by side and approves or corrects in seconds — not minutes. That keeps a human in the loop exactly where judgment is needed, and nowhere it isn't.

We build dedicated logic per document type, because a certificate of insurance, a freight rate confirmation, and a vendor invoice need very different handling. We don't dump everything into one generic model and hope. Each type gets its own extraction targets and validation rules — expiration-date checks on COIs, total-vs-line-item reconciliation on invoices, required-field enforcement on intake forms.

Common types include vendor invoices, certificates of insurance, bills of lading and rate confirmations, patient and client intake forms, and contracts. As new document formats show up, we add them as their own pipeline rather than degrading a shared one.

Black-box extraction that's silently wrong is a liability, so we set explicit accuracy targets per document type, surface confidence scores, and route uncertain cases to humans before anything hits your system of record. The extracted data is delivered wherever you need it — ERP, CRM, accounting, or cloud storage like Drive — via webhook or direct integration, with fields mapped to your destination during the build.

Many of these documents carry regulated or confidential data, so we handle them with SOC-aligned controls, configurable retention you control, and BAAs where healthcare data is involved. Files are never used to train third-party models, and every step is logged for compliance reviews.

The result is a process that's both fast and trustworthy: the model automates the bulk of the volume while people handle only the small slice that genuinely needs judgment. Teams typically eliminate the majority of manual re-keying and cut document turnaround from hours or days to minutes, which unblocks everything downstream — faster billing, faster onboarding, fewer compliance surprises.

Because confidence and exception rates are tracked, you can see exactly how much is flowing through automatically and where the remaining friction is. We tune the pipelines over time so the straight-through rate climbs and the exception queue shrinks.