Prompt as per usual
Use your LLM of choice. TRS integrates directly into your company's AI stack.
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Token Reduction System
Reduce AI costs by 85%
Model classification routes each request to the right level of intelligence before tokens are spent.
Classification routes simple tasks to lower-cost models and reserves premier models for complex work.
Use your LLM of choice. TRS integrates directly into your company's AI stack.
We assign the request to the cheapest model class that can satisfy the task reliably.
Reduce spend by matching each request with the lowest-cost model class that can do the work.
Your workload and provider mix determine the final savings. The estimate excludes implementation costs.
Executive dashboard
Asking every employee to understand model pricing, capabilities, and routing is an impossible training task. TRS makes the decision automatically while the executive dashboard gives leaders one clear view of usage, savings, and policy performance.
TRS optimizes your company's tokens without sacrificing productivity and performance. It reads the request, chooses the right model lane, and keeps simple work out of premier-model paths.
Keep high-intelligence calls for work that actually needs them.
Move simple requests through cheaper routes without changing the product surface.
Give operators a clear policy layer for cost, latency, and quality tradeoffs.
We review your model usage and request mix, then show where lower-cost routes can handle the work.
See which providers and models account for your current spend.
Get a savings range and the routing changes behind it.
About us
co-founder
Jeremy focuses on analytical problem solving, applied AI, and data-heavy systems. As a Machine Learning and Data Science Intern at NT Concepts, he brings technical depth to architecture, modeling, and early product decisions.
co-founder
Sam focuses on the creative side of product: interface feel, user flow, and polished execution. As a Software Engineering Intern at Capital One, he turns ideas into web and mobile products that feel clean and usable.