FutureAI offers a generative application architecture called Masterpiece, which utilizes a dual dataset framework for secure and efficient data processing while enabling developers to create personalized user interfaces. The platform addresses privacy concerns by filtering sensitive user data before contextualization, ensuring a safe and tailored generative experience.
Funding
$5.8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Developing generative AI applications requires managing sensitive user data while ensuring relevant and personalized user experiences. Current methods struggle to balance data privacy with the need for effective contextualization and fast processing.
Solution
FutureAI's Masterpiece is a generative application architecture designed for secure and efficient data processing, enabling developers to create personalized user interfaces. The platform employs a dual dataset framework that filters sensitive user data before contextualization, addressing privacy concerns. Masterpiece utilizes a pipeline to extract sensitive user data, vectorize the remaining data, and ingest it for contextualization. This process pairs user data with application data to generate relevant content within 5,000ms. Developers can select from various versions of the Leo 1 model, including a base model fine-tuned for contextualization, a LoRa-adapted version, or a fully fine-tuned model for optimal performance.
Target Audience
The primary users are developers looking to build generative AI applications that require secure and efficient data processing while providing personalized user experiences.
Features
- Dual dataset architecture for privacy and security
- User Data Pipeline that extracts sensitive data categories such as toxic, derogatory, violent, sexual, and financial information
- Vectorization and ingestion of user data for contextualization
- Integration with Leo 1 models, including Base, LoRa-trained, and Fine-tuned versions
- SDK for prompting users and connecting their data to FutureAI
- Text and multi-modal embeddings for data representation
- Clustering and pairing of user and developer data
- Rapid processing within 5,000ms from data ingestion to interface generation