Operations & Throughput · Use Case Hub

Automate Document Processing with AI.

How to automate document processing with AI across 15 industries with a scoped engagement page. Workflow design, AI agents, governance, and the KPIs (documents per hour, extraction accuracy, exception rate, and processing cost) we report on weekly. Pick your industry below.

Projects from $15k · Refundable 7 days · Kickoff within 5 days

Primary outcome

extract meaning from documents at scale

What we ship

document intake pipeline, extraction schema, validation workflow, and exception queue

KPIs we report on

documents per hour, extraction accuracy, exception rate, and processing cost

What "automating document processing with AI" actually means

Automating document processing with AI is not a single product you buy. It is a workflow you redesign around AI as the operating layer. The agent handles the high-volume, high-structure tasks. Humans handle edge cases, exceptions, and trust-sensitive decisions. The system is instrumented to measure documents per hour, extraction accuracy, exception rate, and processing cost and improve weekly.

What changes by industry is the systems the agent integrates with, the data it retrieves over, the controls it operates under, and the KPIs it has to defend. The architecture is similar; the integration and the controls are different.

The architecture we use for AI document processing

  • Frontier LLM — Claude, GPT-4-class, or Gemini. We benchmark candidates on a labelled test set during Discovery.
  • Retrieval layer over your approved internal sources, with source citations on every output.
  • Tool use for reads and writes against your operational stack (CRM, ERP, ticketing, data warehouse).
  • Reviewer queue for low-confidence outputs. Confidence thresholds set per workflow.
  • Evaluation harness — labelled test set, weekly accuracy reports, regression alerts.
  • Versioned prompts and reviewer-action audit logs for traceability.

Pick your industry

15 industries with a scoped engagement page for document processing. Each is a dedicated build with industry-specific systems, controls, and pricing.

Frequently asked questions

How do you automate document processing with AI?+

We map your existing document processing workflow, identify high-volume and high-structure tasks, build an AI agent that handles those tasks, and route low-confidence cases to a human reviewer. The build connects to the systems your industry already runs on, runs against a labelled test set, and ships behind a reviewer queue before it sees production traffic. We measure documents per hour, extraction accuracy, exception rate, and processing cost from day one and improve weekly.

What is the best AI agent for document processing?+

There is no single off-the-shelf "best" agent for document processing — the right architecture depends on the systems and data of your industry. We typically combine a frontier LLM (Claude, GPT-4-class, or Gemini) with a retrieval layer over your approved sources, tool-use for your stack, and a reviewer queue. We benchmark candidates against a labelled test set during Discovery and pick the model with the best accuracy/cost ratio.

What does AI document processing cost?+

Three phases, billed separately. Discovery sprint: $6k. Build engagement: $20k–$28k. Run retainer: $2.5k–$4k / mo. ~$32k–$58k typical year 1 (60% take the run option for ~6 months). Pricing varies slightly by industry — see the industry-specific pages below.

How long does it take to deploy AI document processing?+

Thin-slice in production in ~6 weeks after Discovery, full Build phase over 6-10 weeks. By day 90, documents per hour, extraction accuracy, exception rate, and processing cost is instrumented and you have a baseline against which to expand to adjacent workflows.

Which industries do you build AI document processing for?+

15 industries listed below have a scoped engagement page for document processing, each with industry-specific systems, controls, and KPIs. Common starting industries include Healthcare Providers, Pharmaceuticals, Medical Devices, Biotechnology, Retail, and others. Don't see yours? We build for any sector — tell us about your workflow and we'll scope it.

What do we own, and what do you own?+

We own workflow design, prompts, retrieval architecture, evaluation harness, and weekly improvement. You own data access, policy, exception approval, and final commercial decisions. At the end of the engagement, every prompt, eval, and config is handed over — no lock-in.

Selected portfolio

Real builds tied to document processing

A rotating selection of engagements where document processing was a primary driver, drawn from our active portfolio. Sectors and scope are accurate; client identities are withheld under engagement NDAs.

Q4 2025 → Q1 2026

Owners-association management SaaS — 55+ screens, 47 normalized tables

Mid-market property operator · GCC region

Full operational backbone for a property operator running multiple owners associations: properties, units, owners, accounting, service charges, budgets, maintenance, violations, and a resident-facing community portal — replacing a patchwork of spreadsheets and disconnected accounting tools.

  • Next.js + tRPC
  • PostgreSQL · Drizzle ORM
  • JWT federated identity

Q4 2025

Internal automation tool — workflow automation for consulting operations

Multi-vertical consulting group · Europe

Internal automation tool to streamline workflows, reduce manual administrative load, and improve operational efficiency across consulting and management processes. Integrates with existing systems rather than replacing them, automating handoffs and document flows that previously moved through email.

  • Workflow automation engine
  • Document-flow integration
  • Operational dashboards

Q2 2026

Internal staff portal — multi-association operations in role-based dashboards

Mid-market property operator · GCC region

Role-scoped portal for property managers, accountants, and maintenance staff. Reuses the OA data model from the management SaaS (zero duplication), adds multi-association switching, maintenance ticket lifecycle, financial reporting, and document storage tied to each association workspace.

  • Next.js + tRPC
  • NextAuth role-based access
  • Drizzle ORM shared schema

Client identities withheld under engagement NDAs. Sector, geography, and scope are accurate. Full case studies on request.

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Start an AI Document Processing engagement

Tell us about your workflow, the systems involved, and the KPI you want to move. We'll send a scoped statement of work within 5 business days.

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