Innrly's marketed AP workflow (submit, review, approve, push to QuickBooks, vendor profiles, duplicate and fraud identification) matches the canonical 2026 shape used by every leading platform, verified against Innrly's own live pages. Their public materials never mention OCR, extraction method, or confidence scoring anywhere. The per-vendor regex parsers that produced four months of wrong totals and missing line items were a hidden implementation choice, not part of the design.
Ace's instinct is confirmed: failing at OCR in 2026 was a choice. Per-vendor template OCR is considered obsolete across the industry, and in the one head-to-head benchmark found (AIMultiple, updated 2026-01, six tools), a general-purpose vision model beat every dedicated OCR product on invoice extraction accuracy. The in-house plan (vision extraction plus confidence scoring plus arithmetic checks plus human approval) is the current state of the art, not a bet on something exotic.
One more thing the research settled: Innrly's "Pay" stage was marketing. Their real workflow ends at approval plus accounting sync, exactly where our V1 ends. We are not shipping less than what THM actually used.
Verified consistent across hotel-vertical platforms (Ottimate, Inn-Flow, M3, Nimble) and horizontal leaders (Stampli, Bill.com, Yooz, Ramp). Cutting payment matches Innrly's actual scope; cutting PO matching is defensible because THM runs no procurement system (M3 delivers matching via its Reeco partnership, which presupposes one).
| Capability (2026 table stakes) | Innrly (as shipped) | Our spec, pre-research | Our spec, now |
|---|---|---|---|
| Email-in invoice capture | Yes | Yes | Yes |
| Layout-proof extraction | No, per-vendor regex | Yes, vision model | Yes, vision model |
| Confidence gate + human review | Promised late, never shipped | Yes | Yes, 95% initial bar |
| Learned GL coding, line level | Partial, GL-in-description complaints | Yes, vendor_gl_map | Yes |
| Duplicate detection | Marketed, never answered Junaid | Yes, sha256 + fuzzy key | Yes, + QBO DocNumber layer |
| Approval routing beyond flat queue | Broken roles, self-approval | Single approver only | Threshold + escalation + delegate |
| Mobile-usable approval | Not evidenced | Unspecified | Responsive web required |
| Per-action audit trail | Not evidenced | Yes, 276/277 pattern | Yes |
| QBO class/location tagging | Descriptions did not even sync | Unspecified | Line-level class, dimension mirror |
| Source PDF attached to the Bill | Not evidenced | Stored, not linked into QBO | Attached via QBO Attachable API |
| Post on approval, not batched | Up to a day, sync button broke | Yes | Yes |
| Payment execution | Marketing only | Out of V1, deliberate | Out of V1, deliberate |
Innrly column sourced from the THM email record (thread "AP Module - Innrly", 42 messages, 2026-03-12 to 06-11) and Innrly's live marketing pages, both read 2026-07-20. Spec columns from the AP Invoice to QBO Pipeline Spec in the vault.
Cost of the additions: roughly one extra build day across Phases 3 and 4 (Woz estimate). The 8 to 12 day envelope from the spec holds.
| Refuted claim | Vote | Why it matters |
|---|---|---|
| Stampli explicitly supports multi-company QBO out of the box | 0-3 | Buying a horizontal tool would not solve our 3-QBO-company plus 12-tracked-entity world cheaply. Strengthens build over buy. |
| OCR-plus-templates is still the accepted incumbent in the hotel vertical | 0-3 | The vertical has already moved to learned extraction. Vision extraction is the mainstream, not a gamble. |
| M3's six-stage procure-to-pay flow is the canonical model | 0-3 | It is delivered through a partner bundle and assumes a PO system. Not a template for us. |
| Nimble ships AP automation as a paid bolt-on | 0-3 | Pricing-structure claim did not hold. Removed from the analysis. |
| Innrly's duplicate detection was a working built-in capability | 1-2 | Marketed on the site, but Junaid asked for it on 2026-03-17 and never got an answer. Treated as unproven. |
Method caveats: most structural findings rest on vendor marketing and education pages; cross-vendor consistency substitutes for a neutral survey. The 95% threshold and Stampli cadence are single-vendor statements, corroborated but not independently benchmarked. The AIMultiple benchmark covered 20 invoices and used an older vision model, so treat it as directional. All pages fetched 2026-07-20.