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Inspired by a conversation on:
The Aerospace Executive Podcast
The Materials Flywheel: How AI is Powering Next-Gen Aerospace w/ Joe Krause
Host: Craig Picken
Timestamp: 00:17:42 - 00:18:09
Found an idea? We can build it for you.
We design and develop SaaS, AI, and mobile products — from concept to launch in weeks.
Direct Quote
"We also have another kind of big push in trying to understand how can you actually deploy these things on-prem for teams that really have serious research operations."
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Sign InHow should I validate this service idea before building it?
2:34 PM
Great question! For a service idea like this, I'd recommend starting with these validation steps:
- Customer interviews: Talk to Technical to understand their pain points
- MVP approach: Build a simple landing page to test demand
- Competitor analysis: Research existing solutions and identify gaps
Would you like me to help you create a specific validation plan for your medium difficulty idea?
2:35 PM
Yes, and what about the technical implementation? Should I build this myself or hire a team?
2:36 PM
Based on your idea's complexity and 3-6 months, here's my recommendation:
Technical Strategy:
- Start with no-code tools for rapid prototyping
- Consider your technical background and available $1,000-$10,000
- Plan for scalability from day one
I can help you create a detailed technical roadmap and resource allocation plan...
2:37 PM
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Sign InSimilar Ideas
AI-Driven Materials Discovery Platform
The business idea revolves around creating an AI-driven platform specifically designed for materials discovery in various industries, particularly focusing on aerospace and defense. This platform could utilize machine learning algorithms to analyze and simulate materials properties and performance, drastically reducing the timeline and costs traditionally associated with materials research. The primary target audience includes aerospace manufacturers, defense contractors, and companies involved in material science. The platform could integrate a user-friendly interface where companies can input their specific material requirements and receive optimized material suggestions, alongside predictive analytics on material performance in extreme conditions. Tactics for implementation could include partnerships with universities for research, leveraging existing labs for experimental validation, and using cloud computing for scalable simulations.