The Enterprise Fight Against Runaway AI Costs

by · Inc42

SUMMARY

  • Indian enterprises are moving beyond AI experimentation, using smarter model routing, agent harnesses and workflow design to reduce the cost of building and scaling AI systems.
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As enterprises increasingly turn to AI to get work done, three new weapons are emerging in their fight to control spiralling AI adoption costs: agent harness, model selection and inference economics.

Simply put, AI adoption is no longer being judged solely on model capabilities, benchmarks or impressive agent demos, but on whether these systems can deliver measurable productivity gains without pushing project costs higher.

As AI moves from pilots into everyday enterprise workflows, the cost of every model call, token, inference and computing resource begins to add up. The bigger question, then, is not simply which model an enterprise uses, but how the entire AI system is designed around it. 

Companies are increasingly looking at ways to reduce unnecessary model calls, route simpler tasks to cheaper models and remove AI from workflows where conventional software can do the job just as well.

This prompted us to ask a sharper question: what actually goes into cutting the cost of an AI project, and which engineering decisions can keep the bill from rising as deployments scale?

Making AI Do More With Less

The first lever is the agent harness, the software layer that manages how an AI agent uses a model. It decides what information the model receives, how a task is broken down and how often the model needs to be called.

This was illustrated in late July when Sarvam AI launched Sarvam Code, a coding agent that divides engineering tasks between planner, worker and verifier agents. Sarvam said the system completed tasks on Terminal-Bench 2.1 at an average cost of about $2, compared with $4.1 to $27.8 for Claude Code and OpenAI’s Codex.

Sarvam also said its system, which routes work between its Sarvam 105B model and a larger open model, reduced serving costs by about 40%.

The point is not that the harness makes the model itself cheaper. Instead, it helps prevent the model from doing unnecessary work.