Hey Product Hunt! I’m Suraj, the maker of ContextOS. AI agents can finish a task while wasting tokens on oversized tool results, repeated reads, and rewriting entire files for small changes. I built ContextOS to help developers find that waste and reduce it—without switching their agent or model. Two tools, one workflow: 🔍 Auditor — see where your tokens and money go. Inspect captured token usage, estimated costs, tool activity, and potential savings in a local dashboard. Free, with guided setup and troubleshooting. ⚡ Optimiser — reduce supported tool waste. Integrate focused tools for targeted edits, selective reads, bounded searches, and eligible repeat-call avoidance. Then compare token usage and task quality against your baseline. Integrations are available for CrewAI, LangGraph, AutoGen, and OpenAI Agents SDK. Try the Auditor without an agent or API key: python -m pip install contextos-auditor contextos-auditor demo --serve The demo uses synthetic data. Run contextos-auditor setup when you’re ready to connect your own agent. Optimiser access: email skj48817@gmail.com for a 90-day free trial. Access and pricing are arranged directly; gated tools require a paid license afterward. A few boundaries matter: Auditor identifies opportunities—it doesn’t automatically optimize runs. Costs are estimates, not invoices. Optimiser savings vary by workload, so task quality needs checking too. Auditor recordings stay local by default, with optional explicitly configured OpenTelemetry export. Where does your agent seem to waste the most tokens—and what would you want ContextOS to help fix first?

Forum Threads

p/contextos-3

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2mo ago

Are AI agent costs stopping you from scaling?

As AI agents move from experiments into everyday operations, token costs become a recurring business expense. A workflow that looks affordable in a demo can be difficult to justify at scale.

I m building ContextOS to make AI agent execution cheaper while preserving useful outcomes. I d love to understand where cost becomes a constraint for you:

Have you limited or abandoned an agent workflow because it was too expensive?

Is the bigger challenge understanding costs, predicting them, or reducing them?

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ContextOS

Save tokens and money on your AI agents

Save tokens and money on your AI agents

Forum Threads

Are AI agent costs stopping you from scaling?

Forum Threads

Are AI agent costs stopping you from scaling?