Torqon
Persistence Context for LLMs with inbuilt Token Reduction
Torqon launched on July 6, 2026 with 4 votes, #6,023 of 24,623 launches that month and more than 75% of that year's launches.
What it does
Your AI forgets everything when a session ends. Torqon fixes that. It's a persistent memory layer for long-conversation LLM systems. Every session starts with context already loaded: projects, decisions, preferences, tech stack. After each message, it automatically extracts and stores new facts about you and your work. Works with Claude Code via hooks, and any MCP-compatible client. No more re-explaining yourself every session. 71.85% token reduction in heavy usage. Set up in under 2 minutes.
Torqon gives your AI assistant persistent memory and context orchestration. It remembers your projects, decisions, and preferences across long conversations, then retrieves and optimizes exactly the right context before requests reach the model.
Connect Torqon to Claude, Cursor, or Windsurf and it remembers your projects, decisions, and tech stack across every conversation. No more repeating yourself. No more lost context. As conversations grow, critical context is lost, token budgets fill with noise, and the model forgets what matters. Upgrade only if you outgrow the free tier. Full plan details, limits, and top-ups on the pricing page . Your data is encrypted in transit and at rest, never used to train models, and deletable anytime from your dashboard. Every message triggers a precise pipeline: extract, embed, retrieve. Zero config. Runs before your model sees a single token. Torqon parses each message to classify intent (store /…from torqon.dev
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