Four pricing model candidates stress-tested against three scenarios. Why the volume-floor subscription model is the recommended path, and how the SR&ED yield calculation changes the math.
The structural problem was diagnosed precisely on the call. SmartOne has real revenue but no committed revenue. Every month's spending is re-decided. The burn math at $100K per month is manageable in theory; it is existential in practice because planning is impossible when revenue is weekly-variable.
The pricing model work is not about raising prices or creating new tiers. It is about converting existing spend-per-month relationships into minimum-floor commitments that let the company plan quarters instead of months.
The B4 research on Canada's SR&ED program is directly relevant to pricing design. A Quebec-incorporated entity with 12 Montreal-based R&D employees and $1.5M in eligible annual R&D spend can generate approximately $801,250 in refundable cash credits per year (federal SR&ED at 35% plus Quebec CRIC at 30/20%). Effective recovery rate on eligible spend: 53%.
This matters for pricing because it changes SmartOne's effective cost base. If $1.5M in qualifying annotation methodology work generates $800K in cash back, SmartOne can offer a more aggressive annual commitment pricing floor than a competitor without SR&ED access. The prerequisite is a Canadian CCPC entity, which SmartOne's Montreal HQ does not yet confirm as incorporated.
Client pays for actual volume consumed each month. No floor, no commitment. Rate is typically per-task or per-hour. SmartOne re-quotes or confirms continuation each month. Client has full optionality to pause, reduce, or exit at any time.
| Scenario | Monthly revenue | Planning horizon | Risk |
|---|---|---|---|
| Upside (robotics pilot expands) | $600-700K | None | Client pauses in month 4 |
| Base (current run rate) | $500K | None | Renegotiation each cycle |
| Downside (Amazon reduces spend) | $200-300K | None | 60% revenue risk in one call |
Client commits to a minimum annual spend (e.g., $600K/year, payable quarterly or in two tranches). Actual usage can exceed the floor; overage is billed at agreed rates. In exchange for committing, the client receives a rate advantage (5-10% discount versus month-to-month), a guaranteed capacity reservation (no queue during ramp events), and a dedicated account management contact. SmartOne gets planning horizon and revenue predictability.
| Scenario | Committed baseline | Planning horizon | Risk |
|---|---|---|---|
| Upside (robotics pilot + 2 new accounts) | $2.4M/yr | 12 months | Over-delivery capacity constraint |
| Base (current 4 warm accounts convert) | $1.2-1.8M/yr | 12 months | One account non-renews at 12 months |
| Downside (only robotics converts) | $600-900K/yr | 12 months | Below burn if no additional growth |
Pricing tied to measurable output quality or downstream model performance. Example: pricing per validated annotation (QA-approved, not just delivered), or pricing per model accuracy improvement metric after training on SmartOne data. Requires clear measurement protocols and shared access to model performance data.
| Scenario | Upside | Downside | Prerequisite |
|---|---|---|---|
| Physical AI buyer with mature evaluation pipeline | Premium pricing, 20-40% over volume rate | Margin risk if QA reject rate rises | Joint measurement protocol signed |
| Startup buyer without evaluation infra | Relationship anchor, preferred vendor status | Revenue variability tied to their model maturity | SmartOne builds basic eval tooling |
| Enterprise with DORA/AI Act compliance requirement | Compliance premium justified by documented provenance | Buyer unwilling to share model performance data | EU AI Act documentation framework built |
A recurring platform access fee (e.g., $15-25K/month) covers the annotation tooling layer, QA dashboard, and data provenance audit trail, with usage-based billing for actual annotation volume. The platform fee stabilizes revenue independent of annotation volume; volume billing upside follows the work.
| Scenario | Platform fee | Volume floor | Year 1 total |
|---|---|---|---|
| Enterprise Physical AI buyer (3 accounts) | $180-300K/yr | $600K/yr | $780K-$900K |
| Mid-market (5 accounts) | $100-150K/yr | $400K/yr | $500K-$550K |
| One anchor enterprise (scaled) | $300K/yr | $1.2M/yr | $1.5M |
| Model | Feasible Phase 1? | Revenue commitment? | Prerequisite | Recommended? |
|---|---|---|---|---|
| A: Spend-per-month | Yes (current state) | No | None | No |
| B: Annual floor | Yes | Yes | Pricing template + commitment language | Yes |
| C: Outcome-based | No | Partially | Measurement infrastructure | Phase 2+ |
| D: Platform hybrid | No | Yes (fee layer) | Platform spec + product layer | Phase 3 |
The annual commitment template (see linked artifact from Role 1.2) is the operational output of this pricing model spec. It contains the actual commercial language, floor structures, and overage mechanics for Phase 1 account conversations.