Disclaimer: Independent product concept by Kaushal Khodifad. Not a live commercial product.return to portfolio
Disclaimer: Independent product concept by Kaushal Khodifad.
DC
DocChunkerSLM
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Enterprise Document Intelligence

DocChunkerSLM

AI extraction with human-in-the-loop governance.
Trust-grade knowledge from your most complex documents.

Teardown anchor · Unstructured.io
Ingestion layer
messy filesclean JSON

Wins throughput - the trust layer is left to you

on top
DocChunker trust layer
rationalechar-provenanceconfidencereview queueaudit trail

The governance a regulated enterprise needs before data touches a decision.

Unstructured.io is a real company in the document-ingestion space. This is an independent teardown by Kaushal Khodifad, not affiliated with or endorsed by Unstructured.io, and the comparison reflects publicly documented scope only.

How It Works

01

Upload

Upload PDF documents

02

Extract

AI extracts entities

03

Review

Human validates each extraction

04

Activate

Approved data enters knowledge store

The governance pipeline

Nothing enters the knowledge store until a human clears it. This is the sandbox, as a flow.

Upload
PDF in
Extract
rationale + span
Provenance-bind
char offsets
Review queue
claim / approve / reject
Activate
knowledge store

Provenance fails to bind → item is blocked from the approval queue; it can be reviewed but never approved.

Enterprise-Grade Capabilities

hosted model · in-VPC is v1

AI Extraction

The extraction model extracts entities with a rationale chain and verbatim source quote.

How it's enforced

The extraction model (hosted via OpenRouter in this demo; an in-VPC small model is the v1 target) extracts entities and clauses, returning a rationale chain and a verbatim source quote for every value.

409-enforced

Human-in-the-Loop Review

Claim, inspect provenance, approve or reject - every extraction.

How it's enforced

Every extraction passes through a governed review workflow. Approve/Edit are rejected at the API level (HTTP 409) when provenance is unverified.

fail = never approvable

Deterministic Provenance

Quoted spans bound to real page + character offsets, server-side.

How it's enforced

The model's quoted span is located inside the parsed PDF text server-side, yielding real page + character offsets. A span that fails to locate is blocked from the approval queue; it can be reviewed but never approved.

trust-grade only

Knowledge Activation

Approved entities enter a queryable, auditable knowledge store.

How it's enforced

Approved entities flow into a governed knowledge store - queryable, auditable, and trust-grade certified. Only human-approved values are ever activated.

3 bound · 3 template

Multi-Schema Support

Schema templates for six industries; three ship fully bound.

How it's enforced

Schema templates for six industries. The bundled demo corpus ships three fully-bound contracts: a Telecom MSA, a Healthcare BAA, and a Finance credit agreement.

append-only

Complete Audit Trail

Every action logged with reviewer, timestamp, and state transition.

How it's enforced

Every action - claim, edit, approve, reject, flag - is recorded with reviewer, timestamp, and state transition. Append-only; no updates or deletes.

Governance is API-enforced, not UI copy
Provenance fails to locate
blocked from the approval queue; it can be reviewed but never approved
Approve without verified span
HTTP 409 rejected
Bulk-approve the queue
Blocked - per-item action only
Any claim/edit/approve/reject
Written as an audit event

Industry Coverage

sample bound - runtime-verifiedtemplate only - awaiting golden set
Telecomsample boundHealthcaresample boundFinancesample boundLegaltemplate onlyInsurancetemplate onlyManufacturingtemplate only

What is real vs. simulated in this demo

Real - enforced Synthetic - illustrative Roadmap - not built yet
PDF parsing + char offsets - REALdetails

PDF parsing, span location, and every page + character offset are recomputed server-side at request time. The review state machine, provenance gate, no-bulk-approve, and claim ownership are enforced by the API (rejections return HTTP 409/400), not by UI copy. Sandbox extraction calls a live hosted model when a key is configured, and says so when it does not.

Sample contracts fictional - SYNTHETICdetails

The three sample contracts are fictional documents authored for this demo - parties, amounts, and clauses are invented. The curated extractions and confidence values are hand-authored, then verified against the real PDFs at runtime; any that failed verification would be downgraded and blocked from approval. Demo review history is synthesised and ephemeral.

Model class - SYNTHETICdetails

this demo runs a frontier LLM via OpenRouter as a capability stand-in; the v1 architecture targets a fine-tuned small model.

SLM-in-VPC deployment - ROADMAPdetails

SLM-in-VPC deployment (weights and text never leaving the customer perimeter) is the v1 target architecture described in the strategy deck. This portfolio demo runs a hosted frontier model via OpenRouter - the opposite deployment mode, disclosed here deliberately.

Ready to explore?

Access the full platform or try the sandbox.

DocChunkerSLM - Enterprise Document Intelligence Platform · the governed trust layer on top of an Unstructured-style pipeline

↑ Independent product concept by Kaushal Khodifad. DocChunkerSLM is an independent product concept by Kaushal Khodifad; it is not a real company or a commercial product. It explores the AI document intelligence space. Not a live commercial product. Data is illustrative.

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