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Case study in preparation

Monetiq: AI and OCR document workflow

An AI solution built around an OCR workflow. The full case study, with the problem, architecture and screenshots, is being prepared.

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No details are published until they are supplied and checked.

Illustrative photo of document review. Not the Monetiq interface.

Case study in preparation

What this case study will cover

Monetiq is being written up from the running product. Each part below is published only once it is supplied and checked, with screens on sample data and no real customer documents.

A desk with three monitors of financial charts overlooking a city at night
A person reviewing printed reports and making notes beside an open laptop
Hands working on a laptop over printed charts on a desk

Illustrative photo. Not the Monetiq interface.

  1. The problemThe business problem in its real environment.
  2. The OCR workflow, step by stepFrom document intake to the reviewed record.
  3. Where AI does the work, and where a person reviewsWhat is automated and where a person stays accountable.
  4. Architecture and technologyThe layers, and the stack once it is confirmed.
  5. Screens on sample dataExported from the running product.
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In-house product. Not a client case study.

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A row of monitors showing operations dashboards and charts
Solution blueprint. Not a client case study.

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Illustrative architectures for problems we are equipped to solve, with the decisions that matter most.

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Have a document workflow that stalls?

Tell us about the workflow. We will tell you honestly what it would take to build.

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