# Execution Scorecard: Auto-filing document scanner for paper-heavy small offices

Score: 65/100

Tier: Needs focused validation

Auto-filing document scanner for paper-heavy small offices scores 65/100 for execution readiness. The recommended next step is Give five small offices a one-week pilot, have them scan a real backlog of 200 documents each, and measure correct auto-classification rate and willingness to pay per seat.

## Bottlenecks
- OCR accuracy on handwriting and poor-quality scans can erode trust if extracted fields are wrong.
- Scanning and storage apps are a saturated category with strong free defaults on every phone.
- A broad AI assistant can flatten differentiation unless the wedge is painfully specific.
- The first release can become a generic dashboard if the job is not named tightly.
- Needs real buyer access, not only desk research.
- Needs proof of budget or repeated urgency.
- Needs a crisp wedge before broad product work starts.

## Accelerators
- Can talk to the buyer before writing much code.
- Can ship a narrow first-win demo quickly.
- Can use local-first research artifacts to keep validation moving without a large team.
- Use specificity as the wedge: one buyer, one workflow, one measurable result.
- Show proof earlier than broad competitors with before-and-after examples and small pilot data.
- Keep implementation lighter than incumbent suites or generic AI assistants.
- Concierge review or paid template

## Dated Launch Plan
- **2026-07-25 / Frame the wedge**: Write the one-sentence promise and test it in the strongest channel. Proof: Give five small offices a one-week pilot, have them scan a real backlog of 200 documents each, and measure correct auto-classification rate and willingness to pay per seat.
- **2026-07-28 / Interview 10 people who match the buyer persona.**: Create the lead magnet and use it to recruit interviews. Proof: Problem resonance: 5+ calls or 10+ detailed replies.
- **2026-08-01 / Ship a clickable demo or concierge workflow that produces the first useful artifact.**: Build the smallest demo that proves the first win. Proof: Activation: 25% of demo visitors complete the first-win path.
- **2026-08-08 / Run one paid pilot or collect explicit pricing objections before automating the rest.**: Delete any report section that feels generic before building. Proof: Commercial pull: 3 paid pilots, LOIs, or concrete procurement next steps.
- **2026-08-15 / Promote to a deeper build plan only after the wedge survives validation.**: Run the lead magnet and first-win demo tests. Proof: Fewer than five qualified buyers agree to discuss the workflow after targeted outreach.
- **2026-08-24 / Execution checkpoint 6**: Promote to deeper implementation only once the wedge survives interviews or paid-pilot outreach. Proof: Promote to a deeper build plan only after the wedge survives validation.

## Builder Prompt
Create a dated execution plan for "Auto-filing document scanner for paper-heavy small offices". Keep the first milestone tied to Give five small offices a one-week pilot, have them scan a real backlog of 200 documents each, and measure correct auto-classification rate and willingness to pay per seat.. Use these bottlenecks: OCR accuracy on handwriting and poor-quality scans can erode trust if extracted fields are wrong.; Scanning and storage apps are a saturated category with strong free defaults on every phone.; A broad AI assistant can flatten differentiation unless the wedge is painfully specific.; The first release can become a generic dashboard if the job is not named tightly.; Needs real buyer access, not only desk research.; Needs proof of budget or repeated urgency.; Needs a crisp wedge before broad product work starts.. Use these accelerators: Can talk to the buyer before writing much code.; Can ship a narrow first-win demo quickly.; Can use local-first research artifacts to keep validation moving without a large team.; Use specificity as the wedge: one buyer, one workflow, one measurable result.; Show proof earlier than broad competitors with before-and-after examples and small pilot data.; Keep implementation lighter than incumbent suites or generic AI assistants.; Concierge review or paid template. Link the output to the Idea Builder prompt and do not expand beyond the first validated workflow.