Empromptu empowers businesses to build full-stack, AI-native applications in minutes—no code required—by combining a conversational builder with powerful agents that handle data ingestion, logic, and deployment.
This is the 2nd launch from Empromptu AI. View more
Empromptu AI
Launched this week
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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Launch Team
the self improving AI angle is really interesting. how do you balance continuous learning with maintaining model stability and consistency? can customers roll back changes if needed?
Empromptu AI
@easton_carter From the technical side, continuous learning and stability are actually in tension by design so we had to solve for both explicitly. The eval is what keeps the model from drifting. Every update gets scored against the same ground truth before it ships so the model can only improve in directions your domain actually validates.
On rollback, yes. Every training checkpoint is versioned so if a learning cycle produces something unexpected you can revert to a previous state. You are never locked into a bad update. The combination of eval gating on the way in and versioned checkpoints on the way out is what makes continuous learning safe enough to run in production environments where consistency actually matters.
Empromptu AI
@easton_carter yes automatic drift detection for the win!
Empromptu AI
@easton_carter yep -- you control your data, your training, which model is running. we want to remove complexity and add powerful deployment capabilities and critical infrastructure to make it easier for more people to build reliable AI they can trust to do actual work
Wion - Audio Dating
Empromptu AI
@tanjum thank you so much yes. We always try to make everything we do accessible.
Empromptu AI
@tanjum Two years of production deployments across healthcare, retail, and financial workflows is what shaped the architecture. The edge cases you only hit in production are exactly what we built around.
CodeSee
@tanjum I’ve seen this in my work too. It’s been hard with the tools to help non technical folks get excited about labeling. But it really is required to get that high level of accuracy
Empromptu AI
@tanjum @joshua_leven thanks so much for the support it's been really incredible bringing this to life
Empromptu AI
@tanjum Exactly! A really common reaction for us is: I feel like this is the perfect conclusion to my Claude Code / Codex projects, a real deployment environment!
Woo, love seeing this ship! Already mulling through some of the fun stuff I could add to my companies in terms of being able to fine tune some models, hah.
Empromptu AI
@holman amazing! Would be super curious to see what you build!!
Empromptu AI
@holman let us know how we can support you!
Empromptu AI
@holman Woo! We're so excited too!
Earth.fm
Empromptu AI
@1mirul thanks so much. If you own your asset you should be able to decide what you do with it whether you compete or whether you decide to sell that asset but you and everyone else should be able to capitalize on the data you own. Your data is getting scrapped and captured anyway. You should at least be compensated
Empromptu AI
@1mirul The compounding part is what makes it structurally different. Most AI deployments get smarter for the vendor. This one gets smarter for you. That asymmetry is the whole point.
Empromptu AI
@1mirul Thanks! We simply believe there's a better way to build great, value-additive functions that are governed entirely by AI, and that the discussion about 'AI costs' is actually a discussion about implementation discipline and tightly controlling deployments around known workflows instead of chaotic experimentation everywhere.
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?
Build Check
This is awesome Shanea! Wish you all the best on this impressive launch
Empromptu AI
@german_merlo1 Thank you so much. Excited to get this out to the world.
Empromptu AI
@german_merlo1 Thank you Germán!
@german_merlo1 Thank you!
Empromptu AI
@german_merlo1 Thanks for the support!
CodeSee
It’s absolutely amazing everything you can build with Empromptu! Custom models are the future — own my data, better accuracy, and cheaper!?
Empromptu AI
@joshua_leven Yes we think it's pretty wild too. We think this gap is the missing link for AI to really take off.
Empromptu AI
@joshua_leven And the cost curve is the part that surprises people most. A smaller model trained on your domain consistently outperforms a general frontier model on your specific tasks at a fraction of the inference cost. You get more accurate and cheaper at the same time!
CodeSee
@sean_robinson1 that’s fantanatic news. Congrats!
Empromptu AI
@joshua_leven Absolutely agree! I can't believe some people are using their macbooks to do complete code implementation harnesses and break away from Claude Code, etc. Entirely.
Maybe someday, but even then I'd prefer to not have to become a full-time AI infrastructure engineer in order to keep my projects going, so it seems only logical something like Empromptu would fill that growing gap.