AI workflow automation platform for document driven operations

A contractor relied on manual processes to transform field data into production-ready documents. The workflow involved reading field information, extracting structured data, applying spreadsheet-based business logic, performing calculations, formatting outputs and reviewing final documents. The process was repetitive and difficult to scale.

The platform combines AI-powered structured extraction, deterministic calculations, business rules, workflow orchestration, human approval, historical-data evaluation and automated document generation.

We deliberately separated AI interpretation from deterministic business logic.

The AI interprets messy information. Software performs calculations. Rules govern execution. Humans approve the result.

Calculations are handled outside the language model. This creates predictable outputs and makes the system easier to test against known results.

Human approval: before the final document is generated, users review and approve the structured output. This provides an operational safety layer for exceptions and unusual inputs.

A frontier language model was benchmarked against representative historical inputs and selected based on extraction quality and workflow performance. The system converts unstructured information into a structured representation that downstream software can process.

The workflow was evaluated against historical datasets to measure how closely AI-generated structured information matched expected outputs.

The workflow significantly reduced document preparation time, eliminated repetitive manual work and improved consistency.

The best AI workflow is rarely one where the language model does everything. It is AI for interpretation, software for precision, rules for control and humans for judgment.