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Manila Times Business

nexos.ai launches smart router, slashing AI coding costs by 60% with a novel benchmarking method

VILNIUS, Lithuania - September 17, 2026 - In 2026, the industry shift toward autonomous coding agents has triggered a "token paradox.” The per unit cost of intelligence has never been cheaper. However, the massive volume of background AI traffic has made AI spend the fastest-growing expense in engineering budgets. Addressing this, nexos.ai has launched its smart router, an intelligent routing capability that automatically matches engineering tasks to the most cost-effective AI models. It routes

Context & Analysis

For Philippine companies already using generative tools in software development, the real issue is no longer whether AI can write code. It is how much that code costs to run at scale. Autonomous coding agents tend to generate many requests behind a single task: planning, testing, refactoring, debugging, and repeated model calls. Even when each request becomes cheaper, total spend can climb quickly if teams default to high-end models for routine work or keep agents running without clear limits.

That is why routing and benchmarking matter. A layer that selects the right model for a given job can reduce waste without forcing developers to choose between speed and quality by hand. For local firms, this is practical, not theoretical. Many Philippine IT-BPO providers, startups, digital banks, e-commerce platforms, and SMEs are already paying for cloud services in dollars while operating in a peso-based cost structure. A meaningful drop in AI coding spend can improve margins, make experimentation safer, and allow smaller teams to build features that would otherwise require larger engineering budgets.

The Philippine angle also touches consumer-facing services. If local fintechs, insurers, and online retailers can use AI more efficiently, they may move faster on product development, fraud checks, customer support automation, and internal tooling. The benefit is not just cost savings; it is the ability to allocate scarce engineering time to business problems rather than managing model calls.

What to watch next is whether such routing tools become standard in enterprise procurement. Companies should ask how models are benchmarked, whether performance can be verified, where data is processed, and whether the router creates another layer of vendor dependence. For financial and consumer-data businesses, the Data Privacy Act still applies even when AI is used internally or through third-party platforms. Expect the competitive edge to shift from simply adopting AI to governing it tightly enough that savings survive in real budgets.

Analysis by IJE Software — original commentary on the story above.

This is an excerpt. Read the full article at the original source:

Source: manilatimes.net

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