Alternatives
Products that do what Perennial does
The AI that remembers everything
- 1
- 2
- 3
- 4
Captures and stores your chat from various AI platforms
Mar 2026 · ai-memory-beta.vercel.app
- 5
- 6
- 7
- 8
- 9
- 10
- 11
- 12AM
Most RAG setups fail because they treat memory like a static filing cabinet. When every transient bug fix or abandoned rule is stored forever, the context window eventually chokes on noise, spiking token costs and degrading the agent's reasoning. This implementation experiments with a biological approach by using the Ebbinghaus forgetting curve to manage context as a living substrate. Memories are assigned a "strength" score where each recall reinforces the data and flattens its decay curve (spaced repetition), while unused data eventually hits a threshold and is pruned. To solve the…
Apr 2026 · github.com
- 13
- 14
- 15
- 16
- 17JA
Hi all! We've built our fair share of LLM apps, everything from Shopify agents to real-time clones of "Samantha" from "Her". We started facing a lot of annoyances & issues repetitively with building functional apps. So we sifted through 97K posts from the OpenAI Community to confirm and find people with similar problems (& we did). It turns out that there are a handful of low-level problems that everybody who is building an AI app that works well needs to solve: statefulness to manage conversations interaction interface between multiple agents and multiple users. robust document search…
2024 · github.com
- 18
- 19BA
Tired of AI coding tools that forget everything between sessions? Every time I open a new chat with Claude or fire up Copilot, I'm back to square one explaining my codebase structure. So I built something to fix this. It's called In Memoria. Its an MCP server that gives AI tools persistent memory. Instead of starting fresh every conversation, the AI remembers your coding patterns, architectural decisions, and all the context you've built up. The setup is dead simple: `npx in-memoria server` then connect your AI tool. No accounts, no data leaves your machine. Under the hood it's TypeScript +…
2025 · github.com
- 20MO
Hey HN! I'm Arindam, part of the team behind Memori (https://memori.gibsonai.com/). Memori adds a stateful memory engine to AI agents, enabling them to stay consistent, recall past work, and improve over time. With Memori, agents don’t lose track of multi-step workflows, repeat tool calls, or forget user preferences. Instead, they build up human-like memory that makes them more reliable and efficient across sessions. We’ve also put together demo apps (a personal diary assistant, a research agent, and a travel planner) so you can see memory in action. Current LLMs are stateless…
2025 · github.com
- 21
- 22
Give your AI a soul — persistent memory that grows with you
Mar 2026 · olivares.ai
- 23SA
I built Syne because I was tired of AI assistants that forget everything after each conversation. Syne is a self-hosted AI agent framework where memory is a first-class citizen — stored as semantic vectors in PostgreSQL, searchable across millions of entries, and persistent forever. Key features: - Unlimited persistent memory with semantic search (pgvector) - Anti-hallucination: only stores user-confirmed facts, auto-deduplicates - Self-evolving: creates new abilities at runtime without restart - Multi-model: switch between Gemini, ChatGPT, Claude mid-conversation - True $0/month setup:…
Feb 2026
- 24
Ranked by how close each launch is in meaning, then by votes. Refine with a description →