AI document automationOsan · Seoul

Documents in.
Validated data out.

TenetCode builds AI document automation for enterprises — reading contracts, filings, and regulatory submissions the way a trained reviewer would, then handing your systems validated data.

Talk to us See how it works
  • MFDS AI drug-approval review R&D — three-year program, active
  • 2026 provider, Korea Tourism Organization Innovation Voucher
  • Designed against the AI Framework Act and FDA-EMA principles

01 — How it runs

Read, structure, validate — then hand off.

See the full pipeline
01 · RecognitionScanned PDF · sample

Service Agreement

Table
Signature
Seal
SAMPLE
02 · DataficationJSON · confidence
Contract date
2026-03-14
0.99
Amount
₩48,000,000
0.97
Term
12 months
0.95
Signature · seal
Needs review
0.86
{
  "contract_date": "2026-03-14",
  "amount": 48000000,
  "term_months": 12,
  "confidence": 0.97
}
03 · AutomationReview → sync
  • No required fields missing
  • Amount and totals cross-checked
  • Confidence ≥ 0.90 on 3 fields
  • Signature · seal at 0.86 — routed to a reviewer

Syncs to

  • ERP
  • CRM
  • Groupware
  • DMS

Auto-processed 3Awaiting review 1

Partners and
active programs

  • MFDSAI drug-approval review R&D
  • Korea Tourism OrganizationTourism Company Innovation Voucher provider

02 — Core technologies

Recognition is only the start.

From document understanding to retrieval, judgment, execution, and compliance review — five technologies wired into one pipeline, end to end.

D.01OCR · LLM

Document understanding

High-accuracy OCR fused with language models to read the context and structure of unstructured documents, then build a standard dataset from them.

  • Skewed · low-res · damaged scansRecognition
  • Tables · charts · signatures · seals · handwritingLayout
  • Mixed Korean-English formsMultilingual
D.02RAG

Knowledge retrieval

Retrieval-augmented generation across internal document and knowledge bases, so answers are grounded in your material instead of the model's priors.

D.03Agent

Agentic execution

Agents that read intent and work context, decide the next step, and carry the task through rather than stopping at a suggestion.

D.04Workflow

Workflow automation

Intake, extraction, validation, and system entry wired into one path. The repetitive middle of the process disappears.

D.05Compliance

Rule-based review

Sector regulation and internal rules encoded so the system checks every required field and flags what is missing before a human sees it.

03 — Where it applies

Built for the documents that carry risk.

The pipeline is domain-agnostic. What changes per sector is the rule set, the target schema, and what counts as an error.

  1. Sector 01

    Finance & Legal

    Documents where an extraction error is a liability. Precise field capture and compliance review on financial and legal paperwork.

  2. Sector 02

    HR, Admin & Contracts

    Repetitive contract review and comparison, plus the employment and benefits records that sit behind every HR request.

  3. Sector 03

    Disclosure, Manufacturing & Quality

    Standard-form documents in quality management and corporate disclosure, where the form itself is the regulation.

  4. Sector 04

    Pharma & Regulatory

    Clinical and non-clinical submissions with dense tables and fixed structures. The domain our MFDS R&D has been built in.

The work is not limited to these four. Any process where documents arrive in volume and the rules for reading them are written down is a candidate.

04 — Work

We don't ship demos.

Each engagement ends with a model, a pipeline, and an operator who can run it without us.

All work
Named client

JUO Company · Pet platform

One identity across commerce, ERP, and AI travel

As the business grew into a pet-adoption franchise, pet-care commerce, and pet travel, we pulled every service's separate member table into one central identity system.

on one account
3 products
auth run in-house
No external IdP
a repo per service
Independent deploys
Read the case

Anonymized · Pharma R&D

Regulatory document AI for a pharma R&D unit

Submission preparation time reduced materially; reviewer time shifted from data entry to scientific judgment.

Read the case

Anonymized · Travel operations

Operations automation for a premium tour operator

Per-trip ops time dropped sharply; the same team now handles a much larger book without adding headcount.

Read the case

05 — Infrastructure

Three primitives. One coherent fabric.

We design networks from three complementary primitives, then compose them around the workload — not the other way around.

Infrastructure in detail

06 — Track record

What we have shipped, in order.

Not a long history, deliberately. Each year added one capability we still run.

  1. 2023Founded

    • TenetCode founded

      Started as a networking and AI systems company for the intelligent era.

  2. 2024

    • LiberDrop released

      Our own zero-storage, end-to-end encrypted file transfer product went to market.

    • Startup & investment support

      Delivered a startup information and community platform project.

  3. 2025

    • MFDS regulatory AI R&D

      Ran an AI R&D project in pharmaceutical approval review.

    • Tourism CRM

      Delivered a customer management project in the tourism sector.

  4. 2026Active

    • MFDS three-year R&D

      Advancing AI-based drug approval review technology under a three-year program.

    • AI pet tour

      Selected as a provider and running the AI pet tour project.

07 — Contact

Start a conversation.

Most of our engagements begin with a 30-minute call. We'll tell you honestly whether we're the right fit.

Headquarters
137 Hansindae-gil, Osan-si, Gyeonggi-do, Republic of Korea
Seoul office
50, Seocho-daero 78-gil, Seocho-gu, Seoul, Republic of Korea

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