DEBCOR Engineering®

DEBCOR AI Packages

Kill Manual Data Entry

Intelligent Document & Transaction Ingestion

Your invoices, orders, and forms arrive as PDFs, EDI files, and emails — and today, someone retypes them. The system reads, validates, and posts them automatically; your people only touch the exceptions.

Straight-through processing rates on real DEBCOR deployments run 80–95%, depending on document quality.

Timeline6–8 weeks to production

Potential value on day one

+$353,600/yr freed

Example — 5 people × $40/hr × 40 hrs × 52 wks × 85% straight-through processing.

Model this with your own headcount below ↓

The value math

Before, after, and what it's worth.

On the left is what it costs to keep doing this by hand. On the right is what happens after the package goes live — and what that frees up on day one.

× $40/hr × 40 hrs × 52 wks (fully-loaded rate — adjust to your own)
Friction keyNo / low frictionMedium friction$Heavy friction$$$

Today

Today · The manual flow

How documents get processed today

  1. 1

    A paper, PDF, or emailed document arrives at the company

    Invoice, order, form, or claim lands via email, EDI, portal, or scan.

  2. 2$

    A human reads the document and prepares to re-key it

    A person opens each one, figures out what it is, and locates the right fields.

  3. 3$$$

    A human manually re-keys every field into your ERP or CRM

    Retype vendor, PO number, amounts, dates, and line items — one document at a time.

  4. 4$

    A human QAs by cross-checking against the PO or contract

    Reconcile line items, chase mismatches over email, wait on approvals.

  5. 5

    A human approves and posts the entry to the books

    Final review, then the transaction posts. Move to the next document.

Human in the loop

One person, full-time, doing this all day — every day of the year.

The hidden cost — human-entry errors

Manual data entry averages a 1–5% error rate — typos, transpositions, wrong PO numbers, decimal-point slips, duplicate payments. Each error costs 10–100× a correct entry to unwind: chargebacks, supplier disputes, audit findings, month-end reconciliation. It doesn't show up as a line on your P&L, but the finance team knows exactly where the time goes.

Yearly expense — today

$416,000/yr

100% payroll burn on manual data entry.
5 people × $83,200 fully-loaded per seat.

After DEBCOR AI

With DEBCOR AI · The automated flow

How it works after the package ships

  1. 1

    The same document arrives — no change for your senders

    Same channels, same formats. Nothing your suppliers, customers, or teams have to do differently.

  2. 2

    AI automatically ingests and recognizes every field

    Multimodal AI reads the document, extracts every field, and runs your validation rules — no human re-keying.

  3. 3

    Anything passing the rules auto-posts straight through

    80–95% of your volume flows straight into your ERP or CRM with no human touch.

  4. 4$

    Ambiguous items route to a human — but only once

    The remaining 5–20% land in a reviewer UI, with the ambiguous field highlighted and the source cited. The AI learns from every resolution — so the same exception never comes back.

  5. 5

    Your straight-through rate climbs over time, on autopilot

    Every human fix compounds into the ruleset. The exception queue shrinks month over month; the freed capital keeps growing.

Human in the loop

One person, part-time, handling only what actually needs judgment.

The error class disappears

Keying-based errors — typos, transpositions, duplicates, wrong-account slips — go to zero. There's no keying step. What survives is only source-document ambiguity, and the exception queue routes those to a human once, with the ambiguous field highlighted and the source cited. Nothing posts at low confidence, and every resolution feeds back into the rules.

Yearly savings — with DEBCOR AI

+$353,600/yr

85% freed15% residual · $62,400/yr

85% of your $416,000/yr labor pool redirected to real work.
Range: $332,800$395,200/yr at 8095% STP.

Directional example, not a quote. Fully-loaded rate assumes $40/hr — swap in your own if it's different. Freed capital = payroll cost the process stops burning, before package fees. Actual value depends on document mix and your straight-through target, set in the scope phase.

What's inside

Everything the package ships with.

Ingestion across every format your business receives — PDFs, images, handwriting, EDI, CSV, XML, JSON, and email

A business-rules validation engine — encode your rules once, apply them everywhere, version them like code

Duplicate detection at ingest, so nothing posts twice

An exception queue with a reviewer UI — humans only touch what needs judgment

Straight-through processing metrics on a live dashboard — STP rate, cycle time, exception rate

A full audit trail per document — every field, every decision, auditor-ready

Sizing & published pricing

Three sizes. One architecture.

Scope compresses down, not features. S-tier is playbook-driven — a single senior engineer delivers against pre-built accelerators inside a fixed configuration boundary. M-tier extends the same systems into landscapes with multiple sources, custom rules, and real integration complexity. L-tier is the full enterprise engagement: dedicated environments, SOC 2 wrap, roadmap co-development, and — for SAP customers — clean-core BTP integration. Same architecture at every size.

Starter

Band

≤ 500 employees · one system, one team

Timeline

3–5 weeks

Published price

from $18k

Scope at this tier

One document type, one system, playbook-driven configuration by a single senior engineer.

Mid-market

Band

500–5,000 employees · multiple sources or rules

Timeline

6–8 weeks

Published price

$65–110k

Scope at this tier

Multiple document types or multiple sources, custom rules, and integration into your ERP.

Large

Band

5,000+ employees · enterprise scope, SOC 2, roadmap co-development

Timeline

8–12 weeks

Published price

$210–350k

Scope at this tier

Enterprise-wide rollout, dedicated environments, SOC 2 wrap, and — for SAP customers — clean-core BTP integration.

Published bands are directional. Final commercial terms are per-client SOW. Managed operations are quoted separately.

Timeline

6–8 weeks from scope to live.

Every package follows the same four-phase delivery. What changes at each tier is the count of sources, rules, and integration surface — not the shape of the work.

  1. Scope

    Week 1

    Sample 200 documents. Agree the extraction schema and business rules.

  2. Build

    Weeks 2–5

    Configure parsers. Deploy the validation engine. Wire exception routing.

  3. Validate

    Week 6

    Parallel run against your existing process. Tune to your STP target.

  4. Live

    Weeks 7–8

    Cutover, plus a 30-day post-launch tuning window on us.

For SAP customers · Bridge to SAP-native

Runs stack-agnostic today — Salesforce, NetSuite, Oracle, a homegrown DB, or any combination. When you move to SAP, the same architecture extends into IDoc and EDI processing without a rebuild — same team, same code. See how DEBCOR extends this into SAP →

Package FAQ

Common questions.

No. It sits in front of your system of record — SAP, Oracle, NetSuite, Salesforce, or a homegrown DB — and pushes clean, validated records into it. Your existing workflow, approvals, and posting rules stay untouched.

Handwriting, faxes, image-only PDFs, EDI variants, spreadsheets with inconsistent layouts — all supported. Multimodal ingestion is the default, not an add-on. We calibrate against your document sample in the first week.

We commit to a straight-through processing rate agreed in the scope phase (typically 80–95%). Anything below that routes to the exception queue for a human to resolve, with the fix fed back into the rules. Nothing gets silently posted at low confidence.

Per-document inference cost is deliberately kept small through a tiered model architecture. A frontier reasoning model runs once per source — during scoping — to derive the extraction and validation rules for your document population. That's a one-time cost, not a per-document cost. In production, retrieval-augmented generation (RAG) against your own rules and prior resolutions handles most decisions first — many never touch an LLM at all. When RAG can't decode a field, a high-efficiency, low-cost model resolves it at fractions of a cent per document. The frontier model is only re-engaged for genuinely novel exceptions the efficient tier can't handle — rare after the first few weeks of runtime. At production volumes, AI inference is a rounding error against the payroll cost it displaces.

Yes. The ingestion, validation, and exception layers are stack-agnostic. When you post into SAP, the same architecture extends into IDoc and EDI processing — same code, same operators, no rebuild.

Scope this package

Fixed scope, fixed price. Tell us the document types and the systems, and we'll come back with a one-page proposal.

Start scoping

Not sure this is the one?

Book a 30-minute fit call with a senior architect. We'll tell you if this is the right package, a different one, or nothing at all.

Book a 30-minute fit call