Document processing that reads the pile so your team does not
Centricone Technologies builds extraction pipelines for the documents your business runs on: classifying what arrived, pulling out the fields that matter, validating them against your own systems, and routing anything uncertain to a person instead of guessing.
The number that matters is not accuracy, it is how much still reaches a person. We tune the confidence thresholds so the pipeline hands over the cases it should, and we report that rate honestly.
support coverage across US and Canada time zones
of code reviewed, tested, and documented before release
The work is reading, retyping, and checking
People are keying in what a machine could read
Invoices, forms, and statements retyped into a system field by field, at a cost that scales exactly with volume and never with value.
Every supplier's layout is different
Template-based extraction breaks on the first vendor who moves a column, and the maintenance burden grows with every new format you accept.
Errors surface downstream, expensively
A wrong figure enters the system silently and is found weeks later in a reconciliation, a dispute, or an audit.
for teams whose inbox is the input
Centricone covers the whole pipeline: ingestion and classification, extraction and validation, the confidence thresholds and review queue, and the reporting that shows what the pipeline is and is not handling.
Deliverables
What you get
- A running pipeline from arrival to validated record
- Classification and extraction across your document types
- Validation rules checked against your own systems
- A review queue with the document beside the field
- Straight-through rate reporting by type and source
- A labelled test set built from your own documents
How an extraction engagement runs
Sample the real pile
A representative set of your actual documents, the messy ones included. The exceptions define the build; the clean examples never do.
Classify and extract against a test set
A labelled set from your own documents, scored from the first week, so accuracy is a number both sides can see rather than an impression.
Validation, thresholds, and the queue
The rules that catch errors and the line that decides what a person sees. Tuned with you, because the right threshold is a business decision, not a technical one.
Run in parallel, then take over
The pipeline runs alongside the manual process until the numbers justify switching, and the review queue absorbs whatever is left.
When document intelligence is the wrong build
This pays for itself on volume and repetition. Without both, the honest answer is usually no.
- The volume is low. A handful of documents a week does not repay a pipeline, however tedious they are to process.
- Every document is genuinely unique — bespoke contracts read for meaning rather than for fields need a lawyer, not an extractor.
- What you need is to ask questions across documents rather than pull fields out of them. That is an enterprise AI assistant.
- The upstream fix is available: if a supplier or portal can send structured data instead of a PDF, take that and skip the problem entirely.
Why teams build extraction with Centricone
Scored against your own documents, messy ones included
Extraction by meaning, not by template coordinates
Validated against your systems before anything is written
Straight-through rate reported honestly
The capability behind this engagement
Model selection and evaluation, extraction architecture, guardrails, and the monitoring and cost controls behind a pipeline like this — covered in more depth on the AI development services page.
Frequently asked questions
Not sure this is the right shape? Tell us the situation and we’ll say which engagement fits.