Distilla, Inc.

Investment teams today rely on a patchwork of tools such as Bloomberg, FactSet, Excel, or ad hoc use of ChatGPT and Perplexity, or attempt to stitch together their own agentic workflows across vendors. This leaves research processes manual, fragmented, and dependent on analyst time for repetitive tasks like earnings analyses, thesis tracking, meeting prep, and watchlist digests. The site frames this as a ceiling on how much research a team can produce, since routine work still consumes analyst and PM attention instead of being offloaded. Firms that keep working this way are described as falling behind competitors who have moved to AI-native research.

Distilla lets a research team encode its research process once and then hand it off to a fleet of specialized AI agents that execute deep-dive analyses end-to-end in minutes or hours. It is described as proactive, delivering outputs such as daily or weekly digests, earnings analyses, thesis tracking, meeting preps, and watchlist summaries on a schedule rather than only on demand. The platform bundles the full stack needed to run this, including data pipelines, agent orchestration, and specialized skills, wrapped in a UX, so teams do not have to assemble this infrastructure themselves. It also indexes news, audio and podcasts, filings, transcripts, and financial data into a knowledge base for agentic retrieval, and personalizes itself over time with a growing memory of a user's preferences and principles.

The site argues urgency directly: "Every quarter you delay is a quarter a competitor doesn't," positioning AI-native research adoption as a competitive necessity happening now.