MeetLoyd reduces token consumption on every agent execution. Less waste, lower costs, smaller carbon footprint — with zero configuration.
LLM providers are competing on price today, subsidized by billions in venture capital. When prices normalize, every wasted token becomes real money. MeetLoyd optimizes now — so you're ready when that day comes.
Fewer tokens per execution means lower LLM bills. Savings compound across thousands of daily agent runs.
Every token has a carbon cost. Reducing consumption cuts your AI operations' environmental impact — measurably.
See exactly how much is saved in the dashboard. Token count, dollar value, CO2 avoided — with a per-source breakdown.
Each layer works independently. Combined, they typically reduce token consumption by 25–40% for agents with rich tool sets.
Agents with 50+ tools don't need every schema in context. Frequently used tools load full schemas; the rest are represented as compact summaries. The right tool is loaded on demand when the agent needs it.
Tools the agent isn't authorized to use are removed from context entirely. Why pay for tokens describing tools that would be blocked anyway? Fine-grained permissions double as cost optimization.
Knowledge graph context is cached in memory for 5 minutes. Consecutive executions for the same agent reuse enriched context without redundant database queries.
The hybrid executor generates a plan with one LLM call, then executes each step mechanically — zero additional LLM calls. A 5-step task that would need 5 ReAct iterations uses just 1. Fewer calls, same result.
When sovereign mode is enabled, content moderation runs on CPU locally instead of calling an external API. Two external round-trips avoided per execution. Near-zero carbon.
Tools are loaded with optimization, unauthorized tools are filtered, context graph is injected from cache when available.
After execution, the platform calculates how many tokens were avoided by each optimization layer. Pure math, no guesswork.
Savings are stored alongside cost data. Every agent has a clear record of tokens saved, dollars saved, and carbon avoided.
The Costs page shows a live savings card with your savings rate, a source breakdown, and per-agent attribution. Exportable for ESG reporting.
LLM inference runs on GPUs. GPUs consume electricity. Electricity generates CO2. Here's how it adds up.
Industry average energy consumption for inference compute per million tokens processed.
Using global grid average carbon intensity. Lower in renewables-heavy regions, higher elsewhere.
Per million tokens of optimized execution. Scale to thousands of daily agent runs and the numbers matter.
Every agent execution is automatically optimized. No config, no add-ons, no extra cost.