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Vendor Evaluation Framework: How to Expose Overhyped OCR and AI Claims from Document Software Sellers

ffiled

2026-02-10

10 min read

Practical vendor rubric and demo tests to expose overhyped OCR & AI claims—run live checks, score accuracy, and lock acceptance into contracts.

Beat the hype: stop overpaying for OCR and AI features that don’t work

Paper piles, missing invoices, and slow signature cycles cost small businesses real time and money. Vendors in 2026 loudly promise “AI-first” document automation and near-perfect OCR, but many features are marketing theatre — fast, glossy demos that fall apart on your real files. This guide gives a practical, repeatable vendor evaluation framework, a weighted scoring rubric, and a suite of live proof tests you can run during demos to expose overhyped claims and choose the solution that actually delivers.

Why this matters in 2026 — trends that change the risk

By early 2026 document vendors have layered generative models, multimodal LLMs, and on-device OCR into their product pitches. Regulatory scrutiny (transparency rules and AI risk guidance introduced across the EU and U.S. in 2024–2025), plus new consumption pricing models (API per-page and per-extraction), make it easy to be surprised by costs and legal exposure. Meanwhile, “OCR as a checkbox” in enterprise suites — and cheaper third-party OCR APIs — means accuracy and integration quality vary widely. You need a simple, measurable way to separate substance from placebo tech.

How vendors typically overclaim: common red flags

Ambiguous accuracy numbers — “99% accurate” with no test set context or definitions (character vs word vs field accuracy).
Studio-quality demos using only pristine PDFs or vendor-curated data.
Undisclosed pre-processing — heavy manual cleanup before OCR is applied.
Opaque AI models — no provenance, confidence scores, or examples of failure modes.
Hidden costs — per-page fees, expensive extraction credits, or e-signature wallet fees.

Framework overview: from discovery to acceptance

Evaluate vendors in five steps: Discovery (requirements & sample set), Live Demo Tests (timeboxed), Proof Test (vendor runs on your seed dataset), Scoring (apply rubric), and Contract & TCO (lock acceptance criteria). Below are the practical tools to run each step.

Scoring rubric — weighted, objective, and actionable

Use a single-page rubric to score demos. The rubric balances accuracy, AI extraction quality, performance, security, integrations, and cost. Weights reflect what matters most to small businesses: getting correct data out and keeping operations flowing.

OCR baseline accuracy — 30%
- Metric: Word Error Rate (WER) or Character Error Rate (CER) on your seed set.
- Scoring bands: >98% = 30 pts, 95–98% = 24 pts, 90–95% = 18 pts, 80–90% = 12 pts, <80% = 6 pts.
Extraction / AI quality — 25%
- Metric: Precision / Recall (or F1) for business-critical fields (invoice number, total, dates, parties, obligations).
- Scoring bands: F1 >0.9 = 25 pts, 0.8–0.9 = 20, 0.7–0.8 = 15, 0.6–0.7 = 10, <0.6 = 5.
Searchability & indexing — 15%
- Metric: Speed and relevance of text search, support for multi-field queries and proximity search.
- Scoring: fast + relevant = 15; slow or partial = 8; poor index = 3.
Security & compliance — 10%
- Metric: SOC 2 type II, ISO 27001, data residency, encryption at rest/in transit, audit logs.
- Scoring: complete coverage = 10; partial = 6; missing key controls = 2.
Integration & UX — 10%
- Metric: Native connectors (QuickBooks, Google Drive, major ECMs), REST API ergonomics, speed of deployment.
- Scoring: ready-made connectors + clean API = 10; some work required = 6; custom build = 2.
Total Cost of Ownership (TCO) & pricing transparency — 10%
- Metric: predictable pricing, clear per-page/feature rates, hardware & migration costs included.
- Scoring: clear & predictable = 10; some unknowns = 6; opaque/usage surprise = 2.

Example: If a vendor scores OCR 24/30, Extraction 20/25, Search 12/15, Security 10/10, Integration 8/10, TCO 8/10, final score = 82/100. Use thresholds: >85 = Strong fit; 70–85 = Good with caveats; <70 = Reject.

Quantify what “accuracy” really means

Ask vendors which accuracy they report: character vs word vs field. Field-level accuracy (did the system capture the invoice number correctly) is what affects operations — not a global “99%” that may hide missing totals or misread tax IDs.

Proof tests to run on vendor demos — practical checklist

Have a prepared seed set of 30–100 documents that reflect your business reality. Include invoices, receipts, contracts, handwritten notes, multi-column statements, and images captured with phones. Never accept a vendor’s curated file set. Run these tests live and timebox each test to 5–10 minutes.

Core OCR tests

Clean printed invoice (single column): expected result – exact invoice number, total, currency, date.
Skewed photo (phone capture, 200–300 DPI) of a receipt: expected – readable merchant, date, total; measure WER.
Multi-column PDF (bank statement): expected – preserve column order and table structure.
Handwritten note (signature line + short memo): expected – identify the typed text only; confirm if handwriting recognition claimed.
Low contrast or faint print (older documents): expected – graceful degradation and a confidence score per field.
Non-Latin script (Spanish with accents, or a second language you need): expected – correct characters and preserved diacritics.

AI extraction & contract tests (run with seeded contracts)

Clause detection: give a contract with explicit auto-renew and termination clauses. Expected: the system flags clause type, extracts the notice period and auto-renew flag.
Obligation extraction: insert a vendor obligation like “Supplier will deliver within 30 days.” Expected: identify party, action, timeline.
Named entity recognition (NER): invoice with vendor name, buyer name (different formats), tax ID — verify entities match exactly.
Summarization prompt: ask the AI for “key risk items” in a 6-page contract. Expected: concise, repeatable summary and link back to the source clause (provenance).
Hallucination test: include a clause that references a fictitious statute. Check if the AI invents statutory text or cites sources correctly.

Search, export & e-signature flow tests

Perform a multi-criteria search (vendor name + date range + amount range). Expected: correct result set within 3 seconds.
Export test: request a JSON export of extracted fields and a search index export. Confirm field names and types are stable (no ad-hoc keys).
E-signature integration: send a contract to sign, track signing audit trail, and verify the signed PDF contains the correct embedded audit metadata (IP/time/order).

Performance & throughput tests

Run a simulated batch: 1,000 mixed pages. Check:

Pages per minute and time to completion.
Error rate and requeue behavior.
API rate limits and error codes.

How to run demos and capture evidence

Require a live, recorded demo with exports. Do not accept only screen-share claims. Ask for:

Raw OCR output (plain text) and structured extraction JSON for every tested document.
Confidence scores per field and per-page OCR confidence.
System logs or processing metadata (timestamps, processing node IDs) when possible.
Signed statement of the exact dataset used for accuracy claims and a reproducible command line or API call you can run yourself.

Record the session. If a vendor resists, treat that as a red flag. You can request the test be run on-site or within a sandbox account you control for final acceptance.

Turning scores into procurement terms: acceptance criteria and SLAs

Convert rubric thresholds into contractual acceptance tests and SLAs. Example clauses to insist on:

Minimum field-level extraction F1 of 0.85 on the agreed seed set for the first 90 days, measured monthly.
Pages processed per minute SLA and maximum retry times for failed pages.
Audit rights to request raw outputs and logs for any disputed document.
Pricing caps on per-page and per-extraction fees, with monthly usage alerts and a three-way reconciliation process.
Data residency and deletion rights aligned to legal/regulatory needs (HIPAA, EU data residency, etc.).

Calculate TCO — what to include (3-year example)

Always model three years. Include:

Licensing and subscription fees (per seat, per month).
Per-page or per-extraction charges; e-signature envelope or transaction fees.
Scanner hardware and maintenance (amortize capital costs over 3–5 years).
Migration costs — one-time data cleaning and ingestion labor.
Storage and backup (hot vs cold), and any eDiscovery or retention hold costs.
Support and professional services (initial setup and ongoing tuning).
Opportunity costs — time saved in retrieval and fewer compliance penalties.

Sample quick TCO calculation (simplified):

Subscription: $600/month = $21,600 over 3 years
Per-page costs: 50,000 pages/year * $0.01 = $500/year => $1,500 over 3 years
Scanner + maintenance: $3,000 hardware + $300/yr maintenance => $3,900
Migration & training: one-time $5,000
Total 3-yr TCO = $21,600 + $1,500 + $3,900 + $5,000 = $31, ~ (rounded) $31,~000

Now compare to measured ROI: if accurate data extraction reduces invoice processing time by 50% and your AP staff cost is $60k/year, you may recover costs in under 12 months. Always map feature performance (from your rubric) to business KPIs.

Two short case studies — real-world application

Case 1: Small accounting firm (12 employees)

The firm received vendor A’s demo touting “bank-grade OCR.” Using our rubric they scored the OCR baseline as 88/100 (field-level F1 0.82). A competitor scored 92/100 but had a per-extraction credit model that doubled costs for high-volume months. The firm negotiated the higher-scoring vendor but added a contractual F1 acceptance test and a volume cap on per-extraction fees. Result: accuracy improved AP turnaround by 60% and costs stayed predictable.

Case 2: Healthcare clinic

The clinic tested two solutions for patient intake forms and signed consents. One vendor’s handwriting recognition failed on real intake notes. The clinic rejected the vendor during the proof test. The selected vendor delivered strong security certifications and a clear retention policy for PHI, satisfying both functional needs and compliance. The clinic reduced storage costs by moving older files to cold storage while keeping indexed, searchable text available for audits.

Negotiation & contract language to protect you

When you’ve selected a vendor, include specific, measurable acceptance criteria in the contract. Examples:

Acceptance test: Vendor will process the agreed seed set within 72 hours and meet a field-level F1 > 0.85. Failure to meet the threshold allows remediation credits or termination.
Transparency clause: Vendor must provide model description, confidence scores, and a changelog for major model updates that affect outputs.
Data portability: On termination, vendor will export all extracted data in JSON and full-text PDFs within 30 days.
Price protection: Annual growth cap on per-page fees and a right to renegotiate if usage-based costs exceed projected budgets by >20%.

Quick-start demo checklist (printable)

Bring a seed set of 30–100 documents reflecting your workflows.
Timebox each test (5–10 mins) and record the session.
Run core OCR tests first, then AI extraction tests on contracts and invoices.
Request raw outputs (text + JSON) and confidence scores.
Run throughput batch (at least 500 pages) to measure pages/min and error rate.
Verify e-signature audit trail and export capabilities.
Score the vendor immediately using the rubric and compare to thresholds.

Practical rule: If a vendor refuses any of these live tests or won’t export raw outputs, assume risk — and price accordingly.

Final takeaways — how to avoid placebo tech

Marketing claims in 2026 will keep accelerating as vendors adopt multimodal AI. Your defense: a concise rubric, a realistic seed set, timeboxed proof tests, and contract-level acceptance criteria. Focus on field-level accuracy, repeatable extraction, transparent pricing, and compliance controls. Document the demo, demand raw outputs, and convert success metrics into contractual SLA items. That’s how you turn sales theatre into reliable workflows that save time and money.

Actionable next steps: assemble your 50-document seed set this week; schedule two vendor demos; run the 90-minute live test and score each vendor with the rubric above. Use the results to negotiate acceptance-based pricing and a 90-day performance guarantee.

Call to action

If you want a printable rubric, a pre-built seed set template, or a TCO spreadsheet tuned for small businesses in 2026, visit filed.store or contact our evaluation team to run a vendor bake-off and deliver the acceptance report you can use in procurement. Don’t buy claims — buy verified performance.

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