Operations analyst
Works the review queue, corrects extractions, and resolves the validation failures the rules raised.
Reading the document is the easy half.
A model pulling the total off an invoice proves very little. The work is everything after it — the checks, the permissions, the uncertain cases, and proving months later how that figure reached the ledger.
A practical delivery path
- 01Receive
- 02Extract
- 03Validate
- 04Review
- 05Route
Use the model for interpretation. Keep the rules, the permissions, the corrections, and the accountability explicit and human.
Extraction inside a controlled workflow.
The system takes documents from email, upload, API, or batch import; classifies them and extracts fields with a confidence signal and the region of the source each one came from; validates the result against business rules and the records it has to match; sends anything uncertain, high-value, or policy-sensitive to a named reviewer; and writes the approved outcome to the system of record with the source, the model output, the correction, and the decision kept together.
Signals that a purpose-built system is the right answer.
- 01
Specialists spend the morning re-typing
Invoices, customs paperwork, certificates, and applications are read and re-keyed by people whose judgment is the reason they were hired.
- 02
Errors are caught downstream instead of at the door
A wrong vendor, amount, or reference passes into finance and surfaces at reconciliation, where correcting it pulls several people away from the work that follows.
- 03
There is no path for an uncertain answer
Output is either trusted wholesale or redone by hand, because nothing routes the doubtful case to a person with the source document beside it.
The processes this has to carry end to end.
- 01
Invoice intake that stops only at the exception
Invoices arrive, match against the purchase order, post when everything agrees, and stop at a reviewer with the discrepancy named when it does not—so attention goes only where the rules could not settle it.
- 02
Extraction with validation gates and human review
We have built document intelligence for an investment consortium: LLM pipelines for parsing, structured extraction, and retrieval-augmented Q&A, with validation gates and human review inside the path rather than beside it.
- 03
Answers that carry their source
Pixelity Agent Builder answers from a defined set of documents using hybrid retrieval with reranking, returns grounded citations, falls back deterministically when the sources do not support an answer, and is measured against a golden set—so an answer can be checked rather than believed.
Screens from a related demonstration.
Captured from Pixelity's fictional product demonstrations. Organizations, people, and records shown are synthetic.
What the system has to do well to be worth building.
- 01
Intake from wherever documents arrive
One queue for email, portal upload, API, and batch import, so nothing is processed out of a personal inbox.
- 02
Extraction shown beside its evidence
Each field displayed against the part of the source it came from, with a confidence signal and its validation status—so a reviewer checks rather than re-reads.
- 03
Rules before review, review before posting
Business rules and record matching run first; what they cannot settle reaches a reviewer who corrects, approves, or rejects with a reason code attached.
- 04
Routing and audit
Approved records sync to the ERP or operations system, and the source, the model output, every correction, and the decision stay linked for as long as policy requires.
Different people need different views of the same operation.
Finance reviewer
Approves high-value and policy-sensitive documents before anything posts, with the source in front of them.
System administrator
Owns the rules, thresholds, routing, and integration health—and reads whether the thresholds are sending too much or too little to people.
Connections designed around who owns which record.
- 01
ERP or accounts payable for vendor master, purchase-order matching, and posting.
- 02
Email and cloud storage for intake and archival, with the archive still the source the audit trail points at.
- 03
Model providers chosen per document type for quality, privacy, latency, and cost—and replaceable without rebuilding the workflow.
- 04
Notification and exception queues, so a document waiting on a person is visible as work.
Controls that protect the operation and the data inside it.
- 01
Document access by role and by entity or customer boundary, enforced on the server rather than hidden in the interface.
- 02
Retention, redaction, and residency rules set by contract and regulation rather than by a provider default.
- 03
Human review required by confidence, value, or policy threshold, with those thresholds written down and adjustable.
- 04
An audit trail linking source document, model output, every correction, and the routing decision that followed.
AI Document Operations
A fictional review workspace: extracted fields beside the source document, uncertain output corrected by a person, and the approved record routed on.
Open the demonstrationRelated concept demonstration
- 01Inbox
- 02Extraction
- 03Validation
- 04Human review
- 05Audit
Delivered one working workflow at a time, not one long build.
- 01
Map the workflow
Document users, records, decisions, exceptions, integrations, and the smallest release that creates measurable operational value.
- 02
Shape the product
Prototype the real screens, permissions, and rules so stakeholders react to a visible system before engineering scope hardens.
- 03
Build in focused releases
Deliver one dependable workflow at a time with testable data, ownership, and reporting—not a long hidden build cycle.
- 04
Release and evolve
Train users on the live workflow, monitor exceptions and adoption, and extend the platform only when the foundation is stable.
Business situations that often lead here.
Articles that help frame the decision.
Tell us the process everyone works around.
Describe it in a sentence or two. We will come back with what we would build first, what it would take, and whether you actually need us for it.