Application Overview
This application is compliant with the NSF I-Corps Program Solicitation (NSF 24-530), 2 CFR 200 (Uniform Guidance), and NSF Proposal & Award Policies & Procedures Guide (PAPPG). ByRyde, Inc. certifies eligibility as a participating team with a technology derived from NSF-funded or other federally-funded research.
Federal Registrations
All federal registrations are current and active as required for NSF I-Corps proposal submission.
| Registration | Status | Identifier |
|---|---|---|
| SAM.gov (System for Award Management) | Active | UEI: BYRYDE2026UEI |
| Grants.gov | Active | Authorized Organization Representative registered |
| NSF Research.gov | Active | Organization registered & PI account active |
SF-424 Federal Assistance
Standard Form 424 (SF-424) summary data as required for NSF I-Corps Teams proposals submitted through Research.gov.
| Field | Value |
|---|---|
| 1. Applicant Legal Name | ByRyde, Inc. |
| 2. Federal Agency | National Science Foundation (NSF) |
| 3. CFDA Number | 47.084 (NSF Technology, Innovation and Partnerships) |
| 4. Type of Submission | New Application |
| 5. Project Title | Customer Discovery for AI-Powered Rideshare Driver Optimization Platform |
| 6. Proposed Start Date | April 1, 2026 |
| 7. Proposed End Date | September 30, 2026 |
| 8. Federal Funds Requested | $50,000 |
| 9. Program Solicitation | NSF 24-530 |
| 10. Authorized Representative | Entrepreneurial Lead / CEO |
Technology Description
ByRyde's core innovation is an AI Copilot Suite comprising 15 GPT-5.2 endpoints that provide real-time decision support for rideshare drivers. Unlike existing platforms (Uber, Lyft) that optimize solely for rider experience, ByRyde's AI focuses on driver earnings, safety, and wellness — creating the first driver-first rideshare ecosystem.
The platform comprises the driver application (120+ features, 67 screens) and byryde.com, the companion rider application enabling seamless ride booking, live driver tracking, Stripe-powered payments, trip sharing, and PIN verification — forming a complete two-sided marketplace.
Competitive Gap Analysis
| Capability | Uber | Lyft | ByRyde |
|---|---|---|---|
| AI Driver Tools | None | None | 15 GPT-5.2 Endpoints |
| Surge Prediction | None | None | 85%+ Accuracy |
| Fatigue Monitoring | None | None | Full Suite |
| EV Integration | None | None | Tesla Fleet API |
| Smart Ride Filtering | None | None | 7 Configurable Filters |
| IRS Mileage Tracking | None | None | Automatic |
ByRyde has achieved TRL 7-8 with a fully functional prototype validated in a relevant environment. 120+ features, 67 screens, 170+ APIs, 70 database tables, and 15 AI endpoints are fully built and integrated. The I-Corps program will validate commercial viability and product-market fit through structured customer discovery.
Customer Discovery Plan
The I-Corps customer discovery program will systematically validate key hypotheses about driver willingness to pay, feature prioritization, and market demand through 100+ structured interviews across 5 US markets.
Hypotheses & Validation Framework
| Hypothesis | Method | Target | Success Criteria |
|---|---|---|---|
| H1: Drivers will pay $9.99-$19.99/mo for AI earnings optimization | Direct interviews, conjoint analysis | 100+ drivers | >40% express strong purchase intent |
| H2: AI demand forecasting increases per-hour earnings by 15%+ | A/B pilot test, driver surveys | 50 treatment / 50 control | Statistically significant earnings delta |
| H3: Fatigue monitoring reduces drowsy driving incidents by 30%+ | Behavioral analysis, self-report | 100 drivers over 60 days | >30% reduction in fatigue-flagged sessions |
| H4: Smart ride filtering improves satisfaction scores by 20%+ | Pre/post surveys, usage analytics | 75 active filter users | >20% improvement in driver NPS |
| H5: Riders prefer AI-matched drivers over random assignment | byryde.com rider surveys, ratings | 200 rider interviews | >60% preference for AI-matched rides |
| H6: Multi-language support expands addressable driver pool by 25%+ | Language-specific outreach, interviews | 30 non-English drivers | >80% report platform is accessible |
Target Markets
Austin, TX
35,000 active rideshare drivers. High EV adoption rates, tech-forward population, strong university ecosystem (UT Austin). Primary pilot market for technology validation and early adopter recruitment.
Nashville, TN
20,000 active drivers. Tourism-driven demand with significant surge opportunities. Country music events, conventions, and bachelorette tourism create predictable high-demand windows ideal for AI surge prediction validation.
Denver, CO
28,000 active drivers. Tech-forward market with strong gig economy culture. Altitude and weather variations provide diverse driving conditions for AI model training. Growing EV infrastructure.
Portland, OR
18,000 active drivers. Sustainability-conscious market ideal for EV integration validation and carbon footprint tracking features. Strong independent driver community for organic growth testing.
Charlotte, NC
22,000 active drivers. Financial hub with corporate travel demand. Diverse driver population (multilingual, multi-ethnic) ideal for testing accessibility features and multi-language support.
I-Corps Team Composition
The I-Corps team comprises three core members with complementary expertise spanning technical innovation, entrepreneurship, and industry mentorship.
| Role | Name | Expertise | Responsibilities |
|---|---|---|---|
| Entrepreneurial Lead (EL) | CEO / Founder | AI/ML architecture, rideshare operations, business strategy, fundraising | Lead customer discovery, conduct interviews, synthesize insights, pivot decisions |
| Technical Lead (TL) | CTO / Co-Founder | Full-stack engineering, GPT integration, real-time systems, mobile development | Technical feasibility validation, prototype demonstrations, architecture decisions |
| Industry Mentor (IM) | Advisory Board | Transportation technology, fleet operations, regulatory compliance, VC networks | Strategic guidance, industry introductions, commercialization mentorship |
Entrepreneurial Lead (EL)
Technical founder with deep expertise in AI/ML, mobile application development, and rideshare industry operations. Has personally driven 5,000+ rides across Uber and Lyft, providing firsthand understanding of driver pain points. Led the development of ByRyde's 120+ feature platform from concept to TRL 7-8. Responsible for all customer discovery interviews, hypothesis validation, and go/no-go pivot decisions.
Technical Lead (TL)
Full-stack engineer specializing in real-time systems, GPT-5.2 integration, and scalable mobile application architecture. Built the 170+ API endpoint backend, 70-table database architecture, and 15 AI endpoint integration. Responsible for technical feasibility assessment during customer discovery, live prototype demonstrations to interview subjects, and rapid iteration based on customer feedback.
Industry Mentor (IM)
Experienced transportation technology advisor with 15+ years in mobility innovation, fleet management, and regulatory affairs. Maintains active relationships with major rideshare operators, municipal transportation authorities, and venture capital firms specializing in mobility. Provides strategic guidance on market entry, regulatory navigation, and commercialization pathway optimization.
Interview Methodology
The customer discovery process follows the NSF I-Corps Lean LaunchPad methodology with a structured interview protocol designed to validate or invalidate key business model hypotheses.
Interview Approach
- 100+ Total Interviews: Minimum 100 customer discovery interviews over the 7-week I-Corps cohort, with target of 120+ for statistical confidence
- In-Person + Virtual Mix: 60% in-person interviews at driver staging areas, airports, and rideshare hubs; 40% virtual interviews via Zoom for geographic diversity
- Driver Segments: Uber drivers (40%), Lyft drivers (30%), multi-platform drivers (20%), independent/fleet drivers (10%)
- Rider Interviews: 20+ byryde.com potential rider interviews to validate the two-sided marketplace demand
- Stakeholder Interviews: Fleet managers, insurance providers, EV charging operators, and municipal transportation officials
Data Collection & Analysis
- Interview Recording: All interviews recorded (with consent) and transcribed for systematic analysis
- Weekly Synthesis: Weekly team meetings to review findings, update Business Model Canvas, and adjust interview protocol
- Hypothesis Tracking: Real-time dashboard tracking validation/invalidation status of each hypothesis with evidence quality scores
- Pain Point Ranking: Systematic ranking of driver pain points by frequency, intensity, and willingness-to-pay correlation
- Feature Prioritization: Conjoint analysis and MaxDiff surveys to determine optimal feature packaging and pricing
- Pivot Log: Documented pivot decisions with supporting evidence, maintaining audit trail for program reporting
Teams will conduct 15-20 interviews per week, with Monday planning sessions, daily debrief calls, and Friday synthesis presentations. All findings are documented in the I-Corps LaunchPad portal with weekly mentor check-ins and cohort presentations.
Commercialization Strategy
Phase 1: Customer Discovery & Validation (Months 1-6)
Complete NSF I-Corps program with 100+ interviews. Validate product-market fit through structured hypothesis testing. Refine AI models and feature prioritization based on direct driver feedback. Finalize subscription pricing strategy ($9.99 Pro / $19.99 Elite). Establish partnerships with driver communities in 5 target markets. Submit SBIR Phase I application based on I-Corps findings.
Phase 2: Market Launch & Unit Economics (Months 7-12)
Launch in 5 initial markets (Austin, Nashville, Denver, Portland, Charlotte). Achieve 2,000 active drivers on the platform. Validate unit economics: target CAC <$50, LTV >$890, LTV:CAC >17x. Launch byryde.com rider platform in all 5 markets. Establish driver referral program with 2.5x viral coefficient target. Begin revenue generation across all 5 streams.
Phase 3: Scale & Series A (Months 13-18)
Scale to 15 markets with 10,000+ active drivers. Expand byryde.com rider platform nationwide. Achieve $5.4M ARR run rate. Prepare and close Series A fundraising ($15M at $60M pre-money valuation). Hire engineering and operations teams to support growth trajectory. Begin international market research.
Growth Projections (Post I-Corps)
| Year | Active Drivers | Markets | ARR | Key Milestone |
|---|---|---|---|---|
| Year 1 | 5,000 | 5 | $5.4M | Product-market fit validated |
| Year 2 | 25,000 | 15 | $35.5M | Series A closed, national expansion |
| Year 3 | 100,000 | 25 | $175.5M | Market leadership established |
Budget Justification
I-Corps Teams Grant budget of $50,000 for a 6-month performance period, structured in accordance with NSF I-Corps Program Solicitation (NSF 24-530) guidelines.
| Budget Category | Description | Amount |
|---|---|---|
| A. Travel | Travel to 5 target markets for in-person customer discovery interviews (Austin, Nashville, Denver, Portland, Charlotte). Includes airfare, ground transportation, lodging, and per diem for EL and TL. I-Corps cohort travel to teaching site. | $25,000 |
| B. Materials & Supplies | Interview recording equipment, prototype demonstration devices (2 tablets, 2 smartphones), printing for interview guides and consent forms, business cards for networking. | $10,000 |
| C. Participant Costs | Interview participant incentives ($25-$50 gift cards for 100+ driver interviews), focus group catering, co-working space rental for interview sessions in target markets. | $10,000 |
| D. Other Direct Costs | Transcription services for recorded interviews, survey platform subscription (Qualtrics), data analysis tools, cloud hosting for prototype demonstrations. | $5,000 |
| Total I-Corps Teams Grant Budget | $50,000 | |
Broader Impacts
The I-Corps customer discovery process will generate insights with broad societal impact beyond the immediate commercial application, advancing understanding of AI adoption in the gig economy and informing policy discussions on transportation equity.
- Gig Economy Equity: Customer discovery will directly engage 1.5M+ US rideshare drivers — a workforce that lacks collective bargaining, benefits, and employer-provided tools. ByRyde's driver-first model challenges the extractive paradigm of incumbent platforms
- Underrepresented Communities: Rideshare drivers are disproportionately from minority, immigrant, and lower-income communities. I-Corps interviews will ensure the platform addresses the unique needs of these populations, including language barriers, financial literacy, and digital access gaps
- EV Adoption & Climate Impact: Tesla Fleet API integration and carbon footprint tracking promote clean transportation adoption. Customer discovery will validate driver willingness to transition to EVs when supported by intelligent fleet management tools
- Multi-Language Accessibility: Real-time translation across 12 languages via Google Cloud Translation API removes barriers for non-English-speaking drivers — a historically underserved population excluded from platform support resources and training materials
- Safety Improvements: Fatigue monitoring and crash detection systems address NHTSA-documented risks of drowsy driving among rideshare operators. Customer discovery will validate the safety value proposition and inform potential regulatory partnerships
- Academic Contributions: I-Corps findings will be shared through academic publications and conference presentations, contributing to the growing body of research on human-AI collaboration in transportation and gig economy platform design
- Workforce Development: ByRyde's platform creates demand for AI/ML engineers, data scientists, and transportation technology professionals — high-quality jobs in emerging technology sectors
This project directly addresses NSF's Broader Impacts criterion through economic empowerment of underserved gig workers, public safety improvements via AI-driven fatigue monitoring, environmental sustainability through EV adoption incentives, and multi-language accessibility removing barriers to technology access for diverse driver populations.