Empromptu AI - Train Fine Tuned Models With AI Apps You're Already Building
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Most AI apps launch on someone else’s model and stay there forever. Empromptu AI turns live AI features into custom models you own. As your app runs, Empromptu AI captures real-world usage, human corrections, and edge cases from live AI workflows, then uses that signal to train a custom model you own. Improve accuracy, lower inference costs, and stop depending forever on rented intelligence from the same providers moving into your category.
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As a tool in the 'Vibe Coding' space, how much control does a user retain over the underlying architecture? If the conversational builder creates the full stack, is there a way to export the code or infrastructure configurations, or are users locked into the Empromptu ecosystem?
@nurlyzhann Yep! We enable you to connect to Github; as you mentioned, many of our users originate in Lovable or Claude Code and so this is a common onboarding pathway.
Incredible pitch, @shanea_leven The absolute best institutional knowledge in any company lives entirely as "tribal knowledge" inside the heads of your senior support reps and operations leads. Turning daily human corrections into a continuous training loop is a massive architectural paradigm shift. Quick question: how does Alchemy handle low-volume edge cases to prevent a few bad human corrections from skewing the model weights?
Parameter efficient fine tuning methods like LoRA have changed the economics of this space significantly does Empromptu leverage these under the hood and does the developer have any control over the fine tuning strategy being applied?
the 'in minutes' claim for full-stack AI native applications is the part that creates the most skepticism. building something that demos well in minutes is straightforward. building something that handles production edge cases, scales appropriately, and doesn't require significant rework when requirements change is a different problem. what does a typical application look like 30 days after the initial build and how much ongoing maintenance does it require from a non-technical user