{"slug": "why-your-memory-api-benchmarks-are-probably-inflated-and-misleading", "title": "Why Your Memory API Benchmarks Are Probably Inflated and Misleading", "summary": "ChatSorter launched a free beta of a persistent memory layer for AI applications that it claims cuts token usage by up to 93% by storing extracted facts and compressed summaries rather than raw conversation logs. The company offers a self-hosted plan, run via Docker or Ollama, where no data reaches its servers, and a hosted plan that stores only extracted content; ChatSorter says it is working toward SOC2 compliance and wipes all stored memories immediately on account deletion. ChatSorter works with any Python backend and any LLM without SDKs or plugins, and scores incoming information for retention, storing high-value items such as a compliance constraint permanently while letting low-value exchanges fade.", "body_md": "## Stop explaining yourself to your AI.\n\nFree beta. No credit card. Set up in under 5 minutes.\n\nEvery new chat, your AI forgets. ChatSorter fixes this by keeping long chats blazing fast, providing a flawless permanent memory layer, and delivering it at a fraction of standard API infrastructure costs.\n\nYou spent three hours getting your AI to understand your project: the context, the constraints, the voice. Then the tab closed. Now you're explaining it all over again. And it's worse than before because you can't remember exactly what you said.\n\nChatSorter sits underneath your AI and keeps the memory alive. Automatically.\n\nType as if you're a user talking to a chatbot. Watch what ChatSorter would automatically remember, without you doing anything.\n\nEspecially the ones your skeptical brain raises before you'd ever sign up.\n\nProvider memory solves one user talking to one product. If you're building your own app on top of the API, their memory doesn't follow your users, it follows theirs. ChatSorter is the memory layer for your app, not theirs. You control what gets extracted, what decays, and which users get which memories.\n\nExtracted facts (name, job, constraints, preferences) and compressed summaries, not raw conversation logs. We never store the full text of messages. On the self-hosted plan, nothing reaches our servers at all, the entire pipeline runs on your machine.\n\nTwo problems: cost and persistence. Sending 200 messages of history on every API call gets expensive fast, up to 93% fewer tokens with ChatSorter. More importantly, long context doesn't survive session boundaries. Once the tab closes, it's gone. ChatSorter's memory persists forever.\n\nSelf-hosted plan means your data never leaves your machine. The hosted plan stores only what's extracted, not raw content. We're working toward SOC2 compliance. If you have strict data requirements now, self-hosted is the answer.\n\nAutomatically. Without you touching anything.\n\n\"What's the weather?\" scores 2. It buffers and fades. \"We can't use EU storage, compliance requirement\" scores 9.8. It gets stored permanently. Noise never competes with signal.\n\nEvery few messages, older context gets compressed into a tight summary. Your AI sees the essential version of what happened, not 400 raw messages it has to wade through.\n\nBefore each AI call, you ask for memories. ChatSorter returns the most relevant ones for that specific moment, not everything, just what the AI needs right now.\n\nThe questions about data security aren't paranoid. Here's how we handle them.\n\nWe store extracted facts and summaries, not the full text of what was said. Your conversations aren't sitting in our database in readable form.\n\nRun the entire pipeline on your own machine. It's free, with no license and nothing that phones home. Your data never leaves your infrastructure.\n\nDelete your account and all stored memories are wiped immediately. No retention periods. No backups we're keeping. Gone means gone.\n\nThe cost saving is real, it's just not the main reason people use it. ChatSorter grows slowly then plateaus. Raw history grows forever.\n\nWorks with any Python backend and any LLM. No SDKs. No plugins. No lock-in.\n\n```\n# After every user message\nrequests.post(\"api.chatsorter.com/process\", json={\n  \"chat_id\": user_id,\n  \"message\": user_message\n})\n\n# Before every AI response: inject only what matters\ncontext = requests.post(\"api.chatsorter.com/search\", json={\n  \"chat_id\": user_id,\n  \"query\":   user_message\n}).json()[\"memories\"]\n\n# Your AI now knows this user across sessions\n```\n\nHost it yourself for free, or let us host it for you.\n\nRun ChatSorter on your own machine or server via Docker or Ollama. Nothing ever touches our servers, and usage is unlimited because it's your hardware doing the work.\n\nWe host it for you. Add an API key and go, no server to manage. Pick a tier below based on how much retrieval volume you need.", "url": "https://wpnews.pro/news/why-your-memory-api-benchmarks-are-probably-inflated-and-misleading", "canonical_source": "https://chatsorter.com", "published_at": "2026-09-12 01:33:35+00:00", "updated_at": "2026-09-12 01:57:25.638709+00:00", "lang": "en", "topics": ["ai-products", "ai-tools", "ai-infrastructure", "large-language-models", "developer-tools"], "entities": ["ChatSorter", "Docker", "Ollama", "SOC2", "Python"], "alternates": {"html": "https://wpnews.pro/news/why-your-memory-api-benchmarks-are-probably-inflated-and-misleading", "markdown": "https://wpnews.pro/news/why-your-memory-api-benchmarks-are-probably-inflated-and-misleading.md", "text": "https://wpnews.pro/news/why-your-memory-api-benchmarks-are-probably-inflated-and-misleading.txt", "jsonld": "https://wpnews.pro/news/why-your-memory-api-benchmarks-are-probably-inflated-and-misleading.jsonld"}}