Dhravya Shah, a 19-year-old Indian-American tech entrepreneur, has built Supermemory, a standardised, open-source evaluation framework and memory layer for context systems that lets developers objectively compare and run memory providers across benchmarks with ease. This tool comes equipped with a Web UI, command-line interface, checkpoints and robust evaluation tools, making it straightforward to assess how different memory systems perform in retaining and recalling context over time — a key challenge in modern AI systems where models often forget previous interactions.

Shah started building Supermemory while balancing intense preparation for competitive exams and early experiments with consumer-facing apps and bots in Mumbai. Over time, the project grew into a powerful framework that attracted attention from developers and AI practitioners seeking better tools for context-aware computing. Supermemory’s design supports switching between memory providers without locking users into one technology, embodying the belief that memory should be model-agnostic and universally accessible in AI development.

The framework can assist a wide range of use cases — from helping tools instantly locate perfect video clips or sift through large file archives for insights to boosting the usability of agents that need persistent memory across sessions. Shah’s vision reflects a broader shift in the AI community toward open, extensible tools that enhance long-term context understanding and personalization, laying groundwork for smarter, memory-capable systems.