Inspiration
There are many powerful AI models available today, but using them often means switching between different platforms, accounts, interfaces, and subscriptions. Different models are also better suited for different tasks, making it difficult for everyday users to know which one to use.
That inspired Vrompt: a unified AI platform built around one simple idea:
One account. One subscription. Multiple AI models.
The goal is to make accessing and switching between AI models simple while giving users one consistent experience.
What it does
Vrompt provides a single AI chat interface for multiple AI models.
In the current version, users can choose an available AI model, enter a prompt, and interact with it from the same interface instead of moving between different AI applications.
The platform is designed so model capabilities can be managed dynamically, creating a foundation for supporting models with different features and limitations.
Vrompt is ultimately about giving users control over which AI they use without making them manage multiple separate platforms.
How we built it
We built Vrompt as a modern web application with the user experience centered around a unified chat.
The frontend handles conversations, model selection, and the overall user experience, while the backend provides the foundation for connecting AI providers and managing model-specific capabilities.
We focused on building the core user journey first:
Choose a model → enter a task → send the request → receive the response.
We also designed the architecture so additional models and capabilities can be integrated without redesigning the entire application.
Challenges we ran into
One of the biggest challenges was creating a unified experience for AI models that don't all work the same way.
Providers can have different APIs, capabilities, context limits, pricing, reasoning options, and supported tools. Vrompt needs to handle these differences while keeping the interface simple for users.
Another challenge was deciding what belonged in the working prototype versus the larger product vision. Instead of trying to implement everything at once, we prioritized a reliable core experience that can be expanded later.
Accomplishments that we're proud of
We're proud of turning Vrompt from an idea into a working foundation for a multi-model AI platform.
Rather than building separate experiences for every provider, we created a unified approach where the model can change while the user's workflow remains familiar.
We also designed Vrompt with expansion in mind, allowing new models, providers, and capabilities to be introduced as the platform evolves.
What we learned
Building Vrompt showed us that providing access to many AI models isn't enough by itself. The real challenge is making those choices simple and useful.
We learned that multi-model AI requires both good engineering and good UX. Users shouldn't need to understand every model specification just to get a useful answer.
We also learned the importance of designing integrations around each model's actual capabilities instead of assuming every AI API supports the same features.
What's next for Vrompt — One AI Platform, Multiple Models
The next major step is Auto — Recommended.
Instead of requiring users to understand every available model, Vrompt will be able to evaluate a task and select an appropriate model based on its capabilities, performance, and cost. Users who want more control will still be able to select models manually.
We also plan to expand provider support and introduce projects, file and image capabilities, web search, usage and credit management, intelligent fallbacks, conversation context management, and subscription plans.
The long-term goal remains simple:
The right AI for every task.
One account. One subscription. Multiple AI models.
Built With
- docker
- nestjs
- nextjs
