We cut >60% of tokens from agentic tasks by removing repeated context

Show HN: All-in-one memory for AI Agents

Operating in show hn launch, We cut >60% of tokens from agentic tasks by removing repeated context operates.

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Every agentic system I see has the same hidden tax: the model keeps rereading the same context.Tickets, Slack threads, docs, customer history, database notes, runbooks, logs, prior decisions. You can cache static prefixes, route to cheaper models, or set team budgets, but none of those fixes the underlying behavior: agents start most tasks trying to re-explore everything.We built Parcle as a shared memory layer for AI agents. It ingests operational context, indexes what happened, and lets agents retrieve a small, relevant memory set for the next step instead of pasting everything back into the prompt - or worse, letting the agent go explore on it's own and burning tokens.We started tracking

The company sits in the show hn launch segment, where it competes on its core product or service.

The company is listed at the Show HN launch stage of development.

Website: parcle.ai/second-brain