Qubrid AI, known for its high-performance GPU Cloud platform, has unveiled a 2-Step No-Code Multimodal Retrieval-Augmented Generation (RAG) as a Service—a mouthful of a name for a potentially game-changing way to make AI chat with your own files, instantly and securely.
Where most chatbots and large language models still live in the static world of pre-trained data (and require tricky prompt engineering to handle custom files), Qubrid’s new service skips the complexity. Users simply drop in their documents, images, or small audio files and start a conversation—no code, no tuning, no lengthy setup.
Your Data, Your AI
“This is the future of AI interaction,” said Qubrid AI CEO Pranay Prakash. “Generic LLMs are powerful, but they’re not built to natively handle your files, verify answers, or merge multiple data types in one conversation. We’ve solved that—while making RAG instant, no-code, and GPU-accelerated.”
Key features at launch include:
- Upload & Chat – Drag-and-drop files and get instant conversational access.
- Trusted Responses – Every answer comes with clickable source citations.
- Multimodal Support – Handles text, images, and small audio in one flow.
Coming soon: smarter organization for multi-session work, advanced reading for scanned/handwritten docs, and model switching for accuracy tuning.
Why It Matters
RAG—Retrieval-Augmented Generation—is increasingly seen as the bridge between powerful general-purpose AI models and business-grade accuracy. By pulling real answers from a company’s own verified data, RAG can sidestep “hallucinations” and boost trust in AI outputs.
Qubrid’s GPU acceleration could be its ace in the hole, delivering faster, scalable results for sectors where speed and precision are critical—think legal review, clinical records analysis, financial research, and high-stakes customer support.
Availability
The beta version of Qubrid’s No-Code Multimodal RAG is available free on the Qubrid AI GPU Cloud platform. You can try it now at platform.qubrid.com/model-studio/rag.
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