## StockAI — Blueprint → Pitch Deck Conversion **The problem in one line:** Independent coffee shops waste money guessing pastry and bean orders; StockAI replaces the guess with a prediction. --- ### STEP 1 — Signal Screen Three claims in the blueprint would not survive investor scrutiny: | Flagged claim | What it becomes | |---|---| | "100% of the independent cafe market in the Pacific Northwest by next year" | Reframed as a market-sizing opportunity statement (TAM/SAM framing), not a market-capture prediction — no company claims 100% share in year one credibly | | "our algorithm is flawless" | Dropped entirely. Replaced with a description of what the model actually uses (weather, local events, historical sales) — the mechanism is the credible claim, not the perfection of it | | "$10M in ARR by year 3" with no shown math | Reframed as an illustrative math path (e.g. "X customers × $Y/month = Z ARR"), not stated as a projection fact, unless you can show the build-up live | --- ### STEP 2 — Slide Map Matrix ``` SLIDE TITLE SOURCE T/O/P TAG 1 Problem Blueprint — food waste from guesswork O 2 Solution Blueprint — prediction engine (weather, O events, sales history) 3 Market Opportunity Reframed from "100% capture" claim — O sized as opportunity, not projected share 4 Traction TRACTION_CONTEXT — 3 beta cafes, 1 T verbal $50/mo commitment 5 Business Model $99/mo subscription (blueprint, stated O as-is — this is a stated price, not a projection, so it carries forward) 6 Ask {ASK} — $500K SAFE, 18mo runway, 2 hires — ``` Adjustment for Angel/Seed audience: standard 6-slide arc, narrative-forward tone, no separate "Financial Projections" slide — the $10M ARR claim is folded into the Ask slide's math path instead of given its own slide, since it can't stand alone without a shown build-up. --- ### STEP 3 — Slide-by-Slide Content **Slide 1 — Problem (O)** Independent coffee shops order pastries and beans by guesswork. That guesswork shows up as thrown-out food and cash tied up in beans that don't move. There's no small-business tool built for this — inventory software exists for grocery chains, not a 12-table cafe. **Slide 2 — Solution (O)** StockAI predicts daily order quantities using weather forecasts, local event calendars, and each shop's own sales history. The owner gets a number, not a spreadsheet: "order 40 croissants, 12lbs of beans" — not a dashboard to interpret. **Slide 3 — Market Opportunity (O)** There are thousands of independent cafes across the Pacific Northwest alone, each currently unserved by inventory tools built for their scale. This is a large, fragmented, underserved market — the opportunity is real; the current claim isn't market share, it's market size, and those are different slides for a reason. **Slide 4 — Traction (T)** Three local cafes are running the beta today, live, for free. One has verbally committed to convert to a paying $50/month customer next quarter. That's a small number and it's tagged that way — three shops is real signal, not proof of scale, and this deck says so rather than dressing it up. **Slide 5 — Business Model (O)** $99/month per shop, direct subscription. Simple, recurring, and priced to be a rounding error against the food waste it prevents — the pitch here is the ROI math for the customer, not a claim about our own revenue trajectory yet. **Slide 6 — Ask** *(see Step 4)* --- ### STEP 4 — Ask Slide Calibration (Angel/Seed — narrative-forward) **The Ask:** Raising $500,000 on a SAFE. **What it buys:** 18 months of runway. Two senior full-stack developers hired. V1 shipped to real, paying customers — not just the three free beta shops we have today. **The math path (illustrative, not a projection):** If StockAI converts even a modest slice of the Pacific Northwest's independent cafes at $99/month, the per-customer economics are strong relative to CAC in a market with no direct competitor at this scale. This is shown as a path, not stated as a year-3 number — the founder should be ready to walk through the actual build-up live (target customer count × price × expected churn), because "10M ARR by year 3" without that math is the first thing an investor will pull on. --- ### STEP 5 — Pre-Pitch Gut Check Pulled from the three Opportunity-tagged (O) slides — these get probed hardest because they're framing, not proof yet: 1. **Market Opportunity:** What's your actual bottom-up TAM/SAM for independent PNW cafes — how many shops, and what's your realistic 3-year penetration assumption, with the math shown? 2. **Solution:** What happens when the prediction is wrong — what's your accuracy today with 3 live shops, and how does the model improve as data accumulates? 3. **Business Model:** At $99/month, what's your actual CAC for an independent cafe, and how does one verbal $50/month commitment translate into a repeatable, priced sales motion at $99? --- **Deck readiness note:** This deck is built on real early signal (3 live beta users, 1 verbal conversion) honestly framed as early-stage, not scaled proof — expect investors to spend most of their questions on the market-size and unit-economics slides specifically because those are opportunity claims, not traction claims; the founder should walk in with the bottom-up market math and CAC assumptions ready to show, not just state.