Frederic Lardinois

Enterprises are hoarding more data than ever to fuel their AI ambitions, but at the same time, they are also worried about who can access this data, which is often of a very private nature. PVML is offering an interesting solution by combining a ChatGPT-like tool for analyzing data with the safety guarantees of differential privacy. Using retrieval-augmented generation (RAG), PVML can access a corporation’s data without moving it, taking away another security consideration. The

DataStax made a name for itself by commercializing the open source Apache Cassandra NoSQL database, but these days, the company’s focus is squarely on using its database chops to build a “one-stop GenAI stack.” One of the first building blocks for this was to bring vector search capabilities to its hosted Astra DB service last summer. Since then, it’s built out more of its stack for building GenAI applications backed by Retrieval-Augmented Generation (RAG) and

Mermaid, the open source diagramming and charting tool, has long been popular with developers for its ability to create diagrams using a Markdown-like language. As is often the case, Mermaid founder Knut Sveidqvist created the project because he saw a need for it in his own job as a software architect and then open sourced it without any immediate plans for monetization. Then, in 2022, he was approached by Open Core Ventures (OCV), the venture

Deepgram has made a name for itself as one of the go-to startups for voice recognition. Today, the well-funded company announced the launch of Aura, its new real-time text-to-speech API. Aura combines highly realistic voice models with a low-latency API to allow developers to build real-time, conversational AI agents. Backed by large language models (LLMs), these agents can then stand in for customer service agents in call centers and other customer-facing situations. As Deepgram co-founder