Delphi, a two-year-old San Francisco AI startup named after the Ancient Greek oracle, was facing a thoroughly 21st-century problem: its “Digital Minds”— interactive, personalized chatbots modeled after an end-user and meant to channel their voice based on their writings, recordings, and other media — were drowning in data.
Each Delphi can draw from any number of books, social feeds, or course materials to respond in context, making each interaction feel like a direct conversation. Creators, coaches, artists and experts were already using them to share insights and engage audiences.
But each new upload of podcasts, PDFs or social posts to a Delphi added complexity to the company's underlying systems. Keeping these AI alter egos responsive in real time without breaking the system was becoming harder by the week.
Thankfully, Dephi found a solution to its scaling woes using managed vector database darling Pinecone.
Delphi’s early experiments relied on open-source vector stores. Those systems quickly buckled under the company’s needs. Indexes ballooned in size, slowing searches and complicating scale.
