Halo Food Co \Australia

**Step 2: Validation - Paid Pilot with 5 Design Partners (Weeks 9-20).** Recruit 5 paying design partners (target: emerging plant-based brands with $1-10M revenue, or mid-sized food companies launching alt-protein lines). Offer 50% discount ($250/month instead of $500) in exchange for weekly feedback calls and case study rights. Expand the platform: add sensory prediction models (train a regression model on 200+ sensory evaluation datasets to predict taste, texture, mouthfeel from ingredient composition), cost optimization (integrate real-time ingredient pricing from suppliers like Ingredion, Kerry Group), and collaboration features (version control for formulations, commenting, approval workflows). Build integrations with common tools (export to ERP systems, generate spec sheets for co-packers). Success metrics: 5 design partners each create 10+ formulations, 2 partners take a formulation to production, NPS >50. Validate willingness to pay and identify must-have features for broader launch.

**Step 3: Growth - Marketplace + Self-Serve SaaS (Weeks 21-40).** Launch two growth engines simultaneously. (A) **Marketplace:** Onboard 20 contract manufacturers and 10 ingredient suppliers. Build a 'Request for Quote' workflow where brands post formulation requirements and manufacturers bid on production. Take 3% transaction fee. This creates a two-sided network effect and generates revenue from day one. (B) **Self-Serve SaaS:** Implement Stripe billing, tiered pricing ($500/month Starter for 50 formulations, $2K/month Pro for unlimited + API access, $5K/month Enterprise for custom models), and PLG tactics (14-day free trial, freemium tier with 5 formulations/month, referral program offering 1 month free). Launch content marketing: publish 'State of Plant-Based Innovation' report with proprietary data from the platform, create SEO-optimized guides ('How to Formulate a Plant-Based Burger in 2024'), sponsor food science podcasts. Goal: 50 paying customers, $50K MRR, 20 marketplace transactions. Prove repeatable customer acquisition and retention (target <5% monthly churn).

**Step 4: Moat - Proprietary Data Flywheel + Advanced AI (Weeks 41-52+).** Build defensibility through compounding data advantages. Every formulation created on the platform generates training data (ingredient combinations, sensory predictions vs. actual results from customer feedback, manufacturing outcomes). Use this to continuously improve models—implement active learning where the AI identifies high-uncertainty predictions and prompts users for validation. Launch 'Umami Insights': a premium analytics product ($10K/year) that gives food companies competitive intelligence (trending ingredients, formulation patterns, white space analysis). Develop advanced features: (1) **Digital Twin Simulator**—partner with a food science lab to collect rheology, extrusion, and cooking data; build physics-informed neural networks that predict how formulations behave during manufacturing and cooking. (2) **Regulatory Copilot**—AI that auto-generates nutrition labels, allergen warnings, and compliance documentation for FDA/FSANZ/EFSA. (3) **Sensory Testing Coordination**—integrate with sensory labs to streamline testing (AI suggests optimal test protocols, analyzes results, recommends formulation tweaks). Raise Series A ($3-5M) to expand team (hire food scientists, ML engineers, sales), build enterprise sales motion (target top 50 food companies), and explore M&A opportunities (acquire ingredient databases, sensory testing companies). Long-term vision: become the 'operating system' for food innovation, where every new product starts with Umami Labs.