Develop Custom AI Builder Platform
Budget: $25 – $50 USD
I’m ready to launch a proprietary AI-driven builder inspired by Lovable and Base44. The vision is a web-based platform where non-technical users can assemble complex assets in minutes while the system quietly orchestrates the heavy lifting—model selection, training, and deployment—behind the scenes.
You’ll guide the entire build: architect the cloud infrastructure, code the core engine, design an intuitive front-end, and wire everything together with robust APIs. Think drag-and-drop creation, reusable templates, realtime previews, and seamless connections to popular third-party tools so that users can publish or integrate their results without touching code. On the AI side I’m open to the mix you feel best suits the goal—classical machine-learning pipelines, contemporary NLP techniques, or computer-vision components—provided they slot cleanly into a modular framework that can grow over time.
To keep us both aligned, here’s how I see the first milestone:
• A clickable prototype showing the user journey from blank canvas to exported output.
• Backend scaffolding with at least one working model endpoint.
• Clear documentation so additional models or UI widgets can be added by any engineer who joins later.
After that we’ll iterate toward a production-ready SaaS, including user authentication, billing hooks, monitoring, and automated model retraining.
If you’ve built end-to-end AI products, understand both Python/ML stacks and modern front-end frameworks (React or similar), and can prove past success scaling to real-world traffic, I’d love to start a technical discussion and map out the sprint schedule.
You’ll guide the entire build: architect the cloud infrastructure, code the core engine, design an intuitive front-end, and wire everything together with robust APIs. Think drag-and-drop creation, reusable templates, realtime previews, and seamless connections to popular third-party tools so that users can publish or integrate their results without touching code. On the AI side I’m open to the mix you feel best suits the goal—classical machine-learning pipelines, contemporary NLP techniques, or computer-vision components—provided they slot cleanly into a modular framework that can grow over time.
To keep us both aligned, here’s how I see the first milestone:
• A clickable prototype showing the user journey from blank canvas to exported output.
• Backend scaffolding with at least one working model endpoint.
• Clear documentation so additional models or UI widgets can be added by any engineer who joins later.
After that we’ll iterate toward a production-ready SaaS, including user authentication, billing hooks, monitoring, and automated model retraining.
If you’ve built end-to-end AI products, understand both Python/ML stacks and modern front-end frameworks (React or similar), and can prove past success scaling to real-world traffic, I’d love to start a technical discussion and map out the sprint schedule.