Building AI for Every Business

AI builders promised that anyone could build sophisticated applications. Some even claimed it would be the last piece of software we'd ever need to build. And here's the dirty little secret: they're full of hallucinations, inaccuracies, and leave you with a ton of work to get it deployed in any business, nevermind an enterprise environment.

I connected with Dr. Sean Robinson, who had developed algorithms for a NASA/DOE Gamma Ray Telescope and led cutting-edge computer vision, anomaly detection and NLP projects. Sean has invented a breakthrough technique for optimizing AI systems that can achieve 98% accuracy versus existing approaches that sit at 60% on average. Initially, we thought we’d help businesses optimize their existing AI applications. But after talking to hundreds of customers, we discovered something unexpected.

We heard the same response every day.

“We do really care about AI accuracy. That’s actually why we haven’t started our AI journey yet. Can you just build us a new accurate AI system from scratch?”.

This pattern repeated across our conversations. Customers wanted our optimization technology but they needed complete AI applications and systems first before they could optimize them. Meanwhile, we found Reddit forums filled with frustration about existing AI builders: f*ck (insert popular AI builder here). We discovered engineering teams that wouldn't risk building AI applications. They couldn't predict if the AI would be accurate, work with their existing infrastructure, or actually solve their internal needs without spending millions of dollars and months of development.

We realized the real problem.

The market was flooded with AI builders that promised speed but couldn’t deliver reliability. These tools are fine for building websites and prototypes but they only create simple applications that connect to APIs. They can’t build real AI applications with the models, optimization and enterprise features that businesses actually need. Even worse, they suffer from fundamental technical problems: context amnesia that forces users to repeat information, static optimization approaches that confuse AI models and black-box architecture that prevent individual control.

So we asked ourselves a key question: can we agentically write all the infrastructure that businesses actually need for production AI applications? Is that technically possible? The answer was yes. Sean’s technique for optimizing AI systems became the foundation for solving all the reliability problems plaguing AI builders.

Because of that, we built something fundamentally different. Instead of static prompts that try to handle every edge case, Sean’s dynamic AI response optimization creates custom prompts for each specific input. This achieves 98% accuracy versus the average industry standard of 60%. We combined this with production-ready infrastructure that businesses need: retrieval-augmented generation (RAG) capabilities, LLMOps tooling, real backends and enterprise features for security and compliance. Something like this is just the beginning

The result: the first complete AI application platform

Empromptu became the first AI builder that delivers complete, enterprise-grade applications from day one. Not just prototypes, but production-ready applications that integrate with existing business systems.

• •Context Engineering That Actually Works - Applications maintain full conversation state and don't suffer from the "context amnesia" that plagues other builders.
• •Dynamic AI Response Optimization - Sean's proprietary technology that creates custom prompts instead of using static approaches that confuse AI models.
• •Individual Task Control - Unlike black-box solutions, you can optimize different workflows within your application separately and are use case agnostic. Each task gets specialized optimization customized to a user’s need instead of one-size-fits-all approaches.
• •Complete Production Stack - Everything businesses need: RAG capabilities, LLM operations accessible with a single click, enterprise deployment options, and integration with existing business infrastructure.

We've moved from selling optimization technology to building complete AI applications for customers, to creating a platform where anyone can build these applications themselves. In record speed, more than 1,000 companies waitlisted for release, and they’re onboarding now as we make the solution fully available. There are some great results already - you're not "seeing" it IS.

Empromptu exists because development teams deserve AI tools that deliver production-ready applications, not just impressive demos that fail when real users interact with them.

This is just the beginning of reliable AI for every business.

I envision a world where a solo founder in rural America can build AI applications as sophisticated as those at Fortune 500 companies. Where healthcare startups can focus on saving lives instead of wrestling with unreliable AI infrastructure. Where the next breakthrough in education, finance, or climate tech isn't held back by AI that works in demos but fails patients, students, or customers. That's the future we're building toward.

When AI builders actually work, innovation becomes democratized.