Business Plan & Roadmap (2025–2028)

An engineering innovation venture for AI-powered wind tunnel testing — bringing real-time aerodynamics to classrooms and research labs.

Overview

Aeronex is a U.S.-based aerospace engineering venture led by Shohanur Rahaman Sunny, a mechanical-aeronautical and industrial engineering graduate from Lamar University with hands-on experience in aerodynamic data systems and test automation. Aeronex modernizes wind tunnel testing in university labs and small research centers with lightweight, AI-powered diagnostic platforms. By combining real-time machine learning, sensor integration, and engineer-friendly dashboards, Aeronex democratizes aerodynamic R&D and improves accuracy across educational and industrial settings.

Phase-Wise Development Plan (2025–2028)

Phase I — Feasibility & Prototype Q1–Q2 2025

Goal: Validate demand and create a modular prototype for AI-driven data reduction.
Activities
  • Analyze use cases from university wind tunnel labs using JR3 internal balances.
  • Develop Python software for real-time data reduction & visualization.
  • Test data cleaning and coefficient prediction on academic datasets.
  • Launch technical blog series and demo videos.
  • Prepare NSF I-Corps and NASA SBIR Phase I submissions.
Deliverables
  • v0.1 Aeronex Core Toolkit (alpha).
  • Draft case study using Sunny’s capstone dataset.
  • White Paper: “AI in Experimental Aerodynamics.”

Phase II — MVP & Pilots Q3–Q4 2025

Goal: Finalize core features and deploy in Texas/Midwest university labs.
Activities
  • Build GUI dashboard for real-time lift/drag visualization.
  • Integrate ML-powered calibration alerts & error detection.
  • Partner with 2+ university departments/clubs for pilots.
  • Collect feedback to refine UI, docs, and export functions.
Deliverables
  • v1.0 Aeronex MVP with JR3 support.
  • Feedback reports from 2+ pilot labs.
  • STEM learning module draft for testing automation.

Phase III — Education & R&D Rollouts 2026

Goal: Expand adoption among academic institutions and applied research groups.
Target Sectors
  • University aerospace/mechanical departments.
  • STEM summer programs and wind tunnel camps.
  • SBIR-funded small aerospace contractors.
Activities
  • Offer low-cost educational licenses with cloud access.
  • Provide integration support and faculty tutorials.
  • Benchmark vs. traditional manual workflows.
Deliverables
  • Deployment case studies from 3–5 academic clients.
  • Time/cost-savings report for aerodynamic testing.
  • Classroom Edition (beta) for simulation & remote learning.

Phase IV — Incorporation & Service Launch 2026

Goal: Establish Aeronex LLC with base in Beaumont, Texas.
Activities
  • Register LLC and set up operations in Beaumont, TX.
  • Publish pricing for education & R&D institutions.
  • Hire initial team (4–6): ML Dev, Systems Engineer, Outreach, Docs/Training.
Deliverables
  • v2.0 Core Toolkit with error-correction & CSV/MATLAB export.
  • Training manuals and onboarding materials.
  • Contracts with 5+ customers.

Phase V — Scale & Federal Outreach 2027–2028

Goal: National STEM platform with training and federal integration.
Activities
  • Apply for follow-on NSF/NASA transition grants.
  • Partner with community colleges for technician training.
  • Offer Aeronex Certification via STEM.org/ASME branches.
  • Engage NASA Space Grant & DoD STEM offices.
Deliverables
  • 25+ academic clients across 10+ states.
  • Certified Training Program with 3+ institutions.
  • Annual impact report (time saved, accuracy, students trained).

Targeted Outcomes by 2028

MetricTarget
Clients onboarded25+ university and lab adopters
High-skilled jobs created10–15 roles (software / R&D / education)
Federal/Private Grants Raised$500K+ (NSF, NASA SBIR, education funds)
AeroML Product Versions3 (Core, Classroom, Certified)
Training Partnerships3+ community college / STEM partners
Testing Efficiency≥ 30% cycle-time reduction vs. manual
Safety & ComplianceLab safety and academic research ethics met

Conclusion

Aeronex is positioned to transform experimental aerodynamics with AI-powered, accessible wind tunnel tools. By addressing inefficiencies in data analysis and enabling real-time testing in educational and small-lab environments, the venture contributes to U.S. interests in STEM education, aerospace R&D, and advanced manufacturing. With strong academic grounding, proven hands-on expertise, and a scalable roadmap, Shohanur Rahaman Sunny’s EB2-NIW-aligned endeavor offers both public benefit and commercial viability.

Aerospace sensors and data acquisition equipment

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