Echoform – unlimited LLM memory via a single 64 KB hypervector
ECHOFORM introduces a novel memory substrate for AI agents, allowing for effectively unlimited long-term memory without consuming context tokens. It utilizes a single 64 KB hypervector to store agent history and provides cryptographic verification for memory retention and deletion. This system is designed to comply with GDPR regulations, offering a proof of data erasure.
- ▪ECHOFORM stores agent history as a single side-channel FHRR hypervector, avoiding the need for context tokens or model weight updates.
- ▪Every recall includes a signed forgetting certificate, providing verifiable proof of what data is retained or deleted.
- ▪The system is model-agnostic and compatible with various AI models, including Llama-3.1 and GPT.
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ECHOFORM Ghost Memory Effectively unlimited long-term memory for any LLM — zero context tokens · zero weight updates · cryptographic forgetting curve. Install · How it works · API · Cloud deploy · Architecture · Provenance If ECHOFORM saves you a context window — drop a ⭐ on the repo. Stars are the only signal that tells us to keep shipping. It takes one click. What is this? ECHOFORM is a production memory substrate for AI agents. Existing systems (Mem0, Zep, Letta, …) treat memory as a retrieval problem — fetch chunks, stuff them back into the prompt, watch the bill scale with episode count.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.