Korea Platform
SystemContact

Document & workflow automation

We design repetitive work such as document classification, data extraction, lookup, and reporting as AI workflows that include human judgment.

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Workflow automation concept image of white document panels passing through a blue glass gate, splitting into two paths, and passing a review frame before being filed
A document flow through classification and review steps

We first separate what AI does from what people check.

Workflow automation is not about attaching a single model. It means redesigning the input, judgment, execution, and approval steps. We separate fixed rules from AI judgment, and set up high-impact actions, such as sending data externally or changing a status, to run only after staff confirm them.

Document AI and AI agents are proposed use cases. The scope of automatic execution is set in a limited pilot (proof of concept, PoC) after we check real data and business rules.

Concept diagramFlow that reaches business systems through human review
Concept diagram of the document & workflow automation flowAI classifies incoming documents such as applications and reports and extracts the fields needed. Staff review only the values that need checking, and only approved results are entered into business systems. Items that are edited or rejected go back to the classification step, and every execution log and exception is recorded.01IntakeForms · Reports · Email02Classify & extractDocument types & fields03Human reviewOnly flagged values04Business systemsSaved or sent on approvalReclassify if edited or rejectedExecution logs, exception handling, and approval records are kept for every stepConcept diagram of the document & workflow automation flowAI classifies incoming documents such as applications and reports and extracts the fields needed. Staff review only the values that need checking, and only approved results are entered into business systems. Items that are edited or rejected go back to the classification step, and every execution log and exception is recorded.IntakeForms · Reports · Email01Classify & extractDocument types & fields02Human reviewOnly flagged values03Business systemsSaved or sent on approval04Reclassify if edited or rejectedLogs · Exceptions · Approvals

When copying and compiling take up the workday

If this sounds familiar

  • When incoming documents are retyped by hand

    We extract the fields you need from applications, reports, and contracts, and show staff which values need checking.

  • When status is compiled across many systems

    We look up and summarize information only from permitted systems to prepare a draft report or a draft for the next task.

  • When it’s unclear who owns automated results

    We clearly separate the steps AI suggests, the steps rules execute, and the steps people approve.

We place AI, rules, and human review in one flow.

Document classification & data extraction

We define document types and the fields you need, and build screens for verifying extracted results and handling exceptions.

Workflow orchestration

We connect multiple steps, such as lookup, summarizing, drafting, and approval, in sequence and based on conditions.

Tool-using AI

We limit the functions AI can use to an allowlist and make inputs, results, and failure handling traceable.

Approvals, logs & exception handling

We add a human check before critical actions and record execution history, errors, and reprocessing procedures on operations screens.

We test small flows first and connect them with approval steps.

  1. We observe repetitive work

    We follow the actual procedure to check how often the work happens, how long it takes, its exceptions, and where staff make judgments.

  2. We test a small flow

    In one or two steps with clear inputs and expected results, we measure accuracy together with the review workload.

  3. We connect to systems in a limited way

    We open only the integrations and permissions needed, and add an approval or confirmation step before status changes and external transfers.

  4. We improve using operating history

    We collect errors, exceptions, and user corrections to adjust rules, prompts, and data structures.

Project deliverables

  • Analysis of current workflows and automation candidates
  • Role split between AI, rules, and people
  • Document processing or agent PoC
  • Definition of integration scope and execution permissions
  • Operating plan for approvals, logs, and exceptions

The exact scope and deliverables are confirmed in early discussions.

View the full project process

This is a proposed use case, not work we have delivered. The video and data analytics projects we have delivered are on the video AI & data analytics page.

View video AI & data analytics

Common questions before a consultation

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Related pages

First AI project: start with a small pilot

Learn how to pick a small task to start with and set evaluation criteria.

Business solutions

Explore the build scope for connecting AI to your existing business systems.

Enterprise knowledge search (RAG)

See how we connect the organizational knowledge that workflow automation needs.

Start by telling us one task where information is copied over and over.

Tell us about your current environment and the work you want to improve, and we’ll help define where to start.

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or+82-2-830-7721kps@openkps.com