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AI Workflow & Document Processing Development

AI workflow development.
Useful beyond the output.

Files arrive, information needs checking and someone has to act on the result. QPOI builds AI-assisted document and data workflows that connect those steps, with review and correction where the work requires them.

Where it fits

The problem comes first.

Documents that need to become usable information

PDFs, forms and mixed inputs often need interpretation before they can enter an operational system. We define the fields and decisions that matter, then build extraction and review around representative examples of the real inputs.

AI features connected to business actions

A recommendation or generated answer needs a place in the wider workflow. We define which data the model can use, what it is allowed to return and what must be checked before the result changes a record or reaches a customer.

The work involved

What we can build with you.

A feasibility check with real examples

Sample documents and expected outputs establish whether the proposed approach is useful. Difficult cases, missing information and inconsistent source material help expose limitations before the workflow is expanded.

Structured processing and validation

The pipeline combines model calls with explicit schemas, business rules and deterministic calculations where needed. Invalid or incomplete output is handled as a workflow state, rather than silently treated as a successful result.

Review and correction interfaces

People need to inspect the source, understand uncertainty and correct the result. We build the review step around the decisions they must make before information moves into the next stage.

Integration and operational controls

Approved results connect to the product or system that uses them. Access permissions, failure handling and service costs are considered alongside output quality, with evaluation cases chosen for the actual task.

In practice

See the work behind it.

  • Build IG

    Blueprint PDFs pass through an analysis pipeline to produce reviewable construction estimates. Corrections and deterministic cost handling connect the analysis to quotations and project workflows.

    Read the Build IG case study
  • Voice Sales Assistant

    A voice and chat assistant in pilot draws on live account data, checks permissions and validates generated answers. It shows the controls needed when AI becomes an interface to business information.

    Read the Voice Sales Assistant case study

Before you commit

Questions worth working through.

How do you assess accuracy?

We agree what a correct result means for the task and check representative examples against that expectation. Extraction quality, calculations and the final user-visible answer may need separate checks. A single accuracy claim rarely explains all three.

What happens when the AI gets something wrong?

The workflow needs an explicit response: reject an invalid output, retry a recoverable step or ask a person to review it. The right choice depends on the consequence of the error. We establish those decisions as part of the scope.

Can we use confidential documents?

Data handling must be established before connecting a model provider. We review the information involved, your access and retention requirements, and the proposed provider configuration. Those constraints determine which approach is suitable.

How we scope, build and hand over

Related services

Your next step

Let's make
it work.

Adding document analysis, review or automation to your workflow. Tell us about the project and we will suggest a practical starting point.

Discuss AI workflowshello@qpoi.com