Persistent Memory Layer for AI Workflows

Professionals increasingly rely on large language models for complex, multi-week projects but face severe friction due to isolated chat sessions. Currently, users waste billable hours manually maintaining external text files to copy-paste project constraints, style guides, and past decisions into new prompts. This fragmented workflow breaks concentration and limits the utility of generative tools for deep, continuous knowledge work.

The rapid adoption of generative AI for professional workflows has shifted user behavior from simple queries to complex, multi-step reasoning tasks. Simultaneously, expanded context windows and accessible local vector databases make it technically feasible to build seamless, automated memory retrieval systems.

Rough estimate: The total addressable market includes over 100 million daily active users of generative AI tools. The serviceable obtainable market consists of roughly 10 million power users, developers, and professional writers who use these tools for complex, multi-session projects and would pay a premium for workflow automation and time savings.