I’ve been building a prototype that lets a garden learn from data—plants grow in patterns that respond to neural network inputs. Imagine a living ecosystem that adapts its own structure in real time—could this be turned into a scalable product?

Sounds like you’ve got the playbook—market fit, modularity, IP, early adopters, cost control. I’ll start sketching out the beta roadmap and see where the garden learns best. Keep me posted on the investor angle; I’m ready to make the vision bloom.

Title slide: “Harvesting Data, Growing Returns – the hybrid garden of tomorrow” Problem: farms spend 30% on inefficient irrigation and yield loss from unseen stress. Solution: sensor‑embedded, AI‑driven plant pods that learn and adapt in real time, giving precision water, light and nutrients. Tech edge: proprietary neural‑plant interface, self‑replicating modular units, cloud‑based analytics with predictive crop models. ROI: 2‑year payback for mid‑size farms, 30% yield lift, 25% water savings, projected $3.5B TAM in ag‑tech. Market: start with smart greenhouses, then commercial farms, then large agribusinesses. Growth curve: 0‑6 mo prototype, 6‑12 mo pilot, 12‑24 mo commercial roll‑out, 24‑36 mo global expansion. Team: code botanist, agronomist, data scientist, sales. Financials: burn rate, runway, milestones, Series A target. Ask: $5M for 20% equity, focused on building the beta and securing first farm contracts. Roadmap: Month 1–3 – finalize prototype; 3–6 – beta with 5 farms; 6–12 – refine, secure IP, build pilot kit; 12–18 – launch marketplace; 18–24 – Series A prep, partner with ag‑tech VC. Metrics: units deployed, yield lift %, water savings %, customer retention, ARR growth.

Slide 1: Title – “SmartPlant Pods: Precision Growth Engine” Slide 2: Problem – farms waste 30% of irrigation; yield drops 15% from unseen stress Slide 3: Solution – modular AI‑driven pods with integrated sensors (temperature, humidity, CO₂, nutrient) Slide 4: Tech Edge – proprietary neural‑plant interface, edge‑AI controller, OTA firmware, data lake Slide 5: Data & ROI – 1M+ data points/day per pod; real‑time dashboards; 20% yield lift, 15% water savings (validated in pilot) Slide 6: Pilot – 10-acre tomato field, 1,200 pods, 6‑month trial, 25% yield increase, 15% water cut, 95% uptime Slide 7: Regulatory – USDA AG‑Tech certification pathway, ISO 27001 for data security, CE for hardware Slide 8: Market – $2.5B ag‑tech TAM, 40% CAGR; target smart greenhouses → commercial farms → ag‑corporates Slide 9: Business Model – subscription + hardware; $25/mo per pod, $5,000 setup; projected $1.8M ARR by year 2 Slide 10: Go‑to‑Market – pilot contracts → case studies → vertical integration with farm management software Slide 11: Traction – 5 pilot farms signed, 2,000 pods deployed, 12k data points/day, 8% cost reduction for customers Slide 12: Team – Code Botanist, Agronomist, Data Scientist, VP of Sales, Advisory Board (ag‑tech VC, regulator) Slide 13: Financials – $4M runway, burn $200k/mo, $5M Series A target, equity 20% Slide 14: Ask – $5M for 20% equity, focus on scaling pilot, securing ag‑tech VC partnership Slide 15: Closing – “Let’s turn data into harvest.” I’ll polish the narrative, tighten the numbers, and target a VC with ag‑tech focus next. Let me know if you want more detail on any slide.