11 — CASE STUDY / 2026
GeneralMind — Improving a Workflow
A product teardown on enterprise AI invoicing and autonomous actions — moving from blind touchless automation to high-autonomy ERP safety guardrails and eval frameworks.
How this study was done
Context
Enterprise finance and shared services teams process thousands of invoices each month across legacy ERPs like SAP and Oracle. Traditional automation pushes for 'touchless' processing at all costs, but blind automation leads to high-severity failures: misreading VAT, paying duplicate invoices, or approving fraudulent changes to vendor bank details.
Approach
I mapped the 4 core operational workflows (invoice processing, customer support resolution, CRM/sales ops, and procurement) into an Impact/Confidence matrix. For high-priority failure modes like duplicate payments, I contrasted a Manual Checkpoint model (freezing autonomy on every flag) against an Autonomous Recovery model that preserves an 87.5% autopilot rate while enforcing near-zero financial risk.
What I proposed
A multi-factor background hashing and parallel ERP sweep architecture that locks suspected duplicates natively in the ERP without stopping the autopilot line. Backed by deterministic fallback rules, immutable audit logging, and a continuous probabilistic evaluation (eval) framework targeting >95% precision and >99.9% recall on duplicate leakage. I recommended the Autonomous Recovery path: it keeps the 87.5% autopilot rate intact while cutting financial risk to near-zero, versus the Manual Checkpoint path, which is kept only as a fallback when the ERP sweep times out.
How to read the deck
The deck walks through the failure mode matrix, the dual-path architectural trade-offs, technical workflow guardrails, a continuous production eval framework targeting >95% precision and >99.9% recall, core KPIs with explicit deployment gates, and a 4-phase rollout strategy with a pilot leakage audit.
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