A platform proposal for two digital products that turn SolarBuddy's real-world impact into a participatory, gamified corporate experience — grounded in UN SDG research and competitive market analysis.
Bay AI recommends treating these as a platform, not two separate apps — the investment in shared infrastructure serves both products and reduces total cost.
The underlying architecture — real-time session management, leaderboard engine, admin panel, event data export — is common to both products. Building them sequentially on the same base reduces total build cost and creates a coherent product family that SolarBuddy owns outright.
The two products address different market segments: Product A targets corporate event facilitators running indoor or office-based team sessions; Product B targets team building providers (TBPs) and corporates running outdoor city experiences. Together, they cover the full spectrum of the SolarBuddy LIVE event market.
Five concepts for the office/event SDG decision experience. Bay AI recommends A1 as the core build, with A4 as a low-cost add-on.
Teams are assigned a real community profile (rural Kenya, coastal Bangladesh, urban Zimbabwe). They make 2–3 sequential decisions about where to direct energy access — each decision routes them down a different SDG pathway. The game calculates a cascading "Ripple Score" showing how one light propagates: one child studying → higher literacy → family income → community health → CO₂ reduction.
On the shared screen, all teams' ripple paths converge in a live animation. The finale shows the room's collective global impact.
Scoring language: All points are expressed in real-world units — "+7,300 study hours", "+80% kerosene reduction", "$140 freed from family budget" — using SolarBuddy's actual verified impact data.
A rapid-fire format designed to run in 20–30 minutes as a conference breakout or event warm-up. All participants join via QR code — one phone per person. Questions appear on the big screen; participants vote individually. Each question is a real-world decision scenario tied to an SDG.
The aggregate of the room's votes creates a "collective decision" and the screen shows the impact rippling outward. Ends with a room-level summary: "This room just generated X impact points — equivalent to Y study hours for Z children."
Teams are each assigned a different SDG as their starting point. Decisions unlock cross-SDG connections — the finale shows a live web of how all 17 goals interconnect across the room.
Teams are "mission operators" managing energy access with a resource budget (tokens = funding, personnel, technology). Mid-game crisis events (storm damage, supply chain issues) disrupt plans. A global leaderboard tracks Impact Efficiency Score — impact generated per resource unit.
Not a single-event game but a multi-session campaign. Three events across a quarter, each a chapter of a longer narrative. Teams carry their community identity and score across all three events. Cumulative impact data becomes powerful ESG annual report content.
Five concepts for the GPS-guided city exploration experience. Bay AI recommends B1 as the standard SKU and B4 as the premium enterprise product.
GPS-guided city exploration where each checkpoint is tied to an SDG theme found in the physical environment. At a park: SDG 15 challenge. At a local market: SDG 8 challenge. At a landmark: SDG 11 challenge.
Each challenge completed generates a virtual "impact token" tied to that SDG, contributing to the team's SDG portfolio. The team with the most diverse SDG portfolio wins — not just the most points.
Multiple teams in multiple cities join the same session simultaneously. Each city has its own local checkpoints, but all teams compete on the same global leaderboard — Sydney completing SDG 13 challenges at a beach, London completing SDG 11 at a green building, New York at a library for SDG 4.
A shared screen in each room shows all cities' progress updating in real time. The finale reveals which city contributed most to the global SDG portfolio.
Time-pressured city race with a meta-game: teams that take longer to discuss decisions get higher impact scores; teams that rush get lower impact. The final winner is determined by a composite Speed + Impact score.
Teams play development consultants auditing a fictional city. They collect "evidence cards" at real locations, then present recommendations to a "board" — other teams vote on the best plan. The winning team's recommendations are notionally funded.
AR overlays at real locations reveal stories of communities served by SolarBuddy. Fully cooperative — teams collectively uncover a set of community stories. Ends with a shared gallery of real-world impact.
Product A: Build A1 (The Ripple Engine) as the core experience. Add A4 (Lights On) as a conference-energiser SKU on the same engine at low incremental cost.
Product B: Build B1 (SDG Trail) for the standard city explorer, and B4 (Global Impact Sprint) as the premium multi-city SKU. B4 is the product that justifies the "Race Around the World" concept and has the highest enterprise sales potential.
Phase 2: Plant B5 (AR) and A5 (World Builders) in the proposal as future directions — they demonstrate ambition without committing to complex build in Phase 1.
Three options were considered. Bay AI recommends Option 3 for Product A and Option 1 or 2 for Product B.
All figures are indicative and in AUD unless otherwise noted. Final scope and pricing follow a discovery workshop.
| Phase | What You Get | Indicative Range (AUD) | Timeline |
|---|---|---|---|
| Phase 1 | Product A MVP — web app, community profiles, 2–3 decision points, Ripple Reveal finale, basic admin panel, post-event data card | $35K – $55K | 10–14 weeks |
| Phase 2 | Product A full — native app, multi-location sessions, TBP admin layer, individual voting, post-event notification, ESG data export, A4 conference SKU, white-label branding | +$40K – $65K | 16–24 weeks |
| Phase 3A | Product B — City Quest via white-label platform + custom SDG layer (recommended path) | $18K – $28K | 8–12 weeks |
| Phase 3B | Product B — City Quest, fully custom on shared platform | $30K – $48K | 14–20 weeks |
| Phase 1–3A total | Full dual-product suite via most efficient path | ~$88K – $133K | ~24–36 weeks |
These remain unresolved and will determine the scope of the fixed proposal Bay AI produces after the discovery call.
Even a rough signal ("low five figures" vs. "$150K") determines whether we scope Phase 1 alone, or present Phase 1 + 2 as the starting package. Without this, the cost table above is the honest range.
Does a TBP-facing admin panel need to be in Phase 1, or can we start with SolarBuddy-staff-only and add the partner layer in Phase 2? The difference is roughly 3–4 weeks of build time and $8,000–$15,000 AUD.
Bay AI recommends addressing both in a short discovery call before any build begins.
We've structured this as a platform investment, not a one-off project, because that's what maximises SolarBuddy's long-term return. A white-label tool gets you to market faster but limits your product.
We researched the competitive landscape so you don't have to sell to your exec team based on intuition — you can show them exactly where the gap is and why SolarBuddy fills it uniquely.
The emotional core of SolarBuddy — one light, one child, one ripple — is what makes this product worth building. Bay AI's job is to make sure every technical decision serves that story.