1 Task at 0.005 Yen — Do You Understand What This Means?

It costs 0.005 yen to process one back-office task. Yes, that’s 0.005 yen in Japanese yen. You are not misreading the digits.

This is the figure released by the AI agent OS “Qualixar OS.” It integrates over ten large language models and more than eight agent frameworks to automatically assign and execute tasks. The average cost per task is $0.000039.

What is happening in the back offices of SMEs today? An accountant is processing invoices for a monthly salary of 250,000 yen. An HR officer is managing attendance for 220,000 yen a month. A sales clerk is preparing estimates for 200,000 yen. A world where these “routine tasks” can be replaced by AI agents costing a few thousand to tens of thousands of yen per month is already upon us.

A turning point from “hiring people” to “hiring systems.” This is not a metaphor; it is a matter of cost structure.

What Has Changed — The Concept of “Orchestration”

AI agents themselves are not new. Asking ChatGPT to “write a reply to an email” is a typical use of an agent. So, what has changed?

An “OS” that integrates multiple agents to automate entire workflows has emerged.

The mechanism of Qualixar OS works like this: for example, “When an invoice arrives, read its contents, input it into accounting software, notify the approver via Slack, and generate transfer data once approved” — this entire sequence is handled by multiple AI agents. The only task for humans is to define the workflow initially. After that, it runs on its own.

Traditionally, such automation was the realm of RPA (Robotic Process Automation). However, RPA had a fatal weakness: it would stop working if the screen layout changed, it couldn’t handle exceptions, and it required hundreds of thousands of yen to implement. SMEs could not afford it.

AI agent OS fundamentally solves this problem. It understands tasks in natural language, adapts to screen changes, and makes decisions in case of exceptions. Moreover, the cost is drastically lower. The implementation cost of RPA at 3 million yen can be reduced to a few tens of thousands of yen per month. This is not an “improvement” but a “structural transformation.”

Autonomous Development with Jira Integration — What a 95% Success Rate Means

Another noteworthy technology is autonomous software development using AI agents.

An autonomous development system integrated with Jira manages about 1,602 lines of backlog and automatically processes tasks. The success rate is 95%. This means that 95 out of 100 tasks are completed without human intervention.

What does this mean for SMEs? For instance, if you create a ticket in your internal business management tool saying, “I want this feature,” the AI agent reads that ticket, writes the code, tests it, and deploys it. The only human tasks are writing the ticket and doing the final check.

Traditionally, such custom development would cost between 500,000 to 2 million yen if outsourced. Hiring an in-house engineer would cost over 6 million yen annually. With AI agents, however, it could potentially run for a few tens of thousands of yen per month.

However, there is a caveat. A 95% success rate means that 5% could fail. If that 5% involves authentication or data processing, it could lead to critical bugs. Therefore, a design of “95% automation + 5% human verification” is more realistic.

AgentGate — Traffic Management Between Agents

When multiple AI agents operate simultaneously, the issue arises of “who does which task.” Optimizing this is the role of “AgentGate,” a lightweight routing engine.

The mechanism is simple. When a request comes in, it determines whether it can be processed by a single agent or if collaboration among multiple agents is needed, and appropriately routes it. This reduces unnecessary API calls and optimizes costs.

What is crucial for SMEs is that this routing enables a “pay-per-use” model. When hiring people, the salary remains the same whether they are busy or idle. With AI agents, if there are no tasks, the cost is nearly zero. You can ramp up operations only during busy periods.

You can fully activate agents only during the peak times for invoice processing at the end of the month and minimize their use at other times. This realization of “variable labor costs” is significant for SMEs, allowing them to escape the structure where fixed costs burden management.

What SMEs Should Do Now to “Hire Systems”

So, what should you start with specifically? Here are three steps to consider.

1. Inventory Your Back-Office Tasks by “Task Units”

First, list the tasks in accounting, HR, and sales administration by task units. Break them down into units like “inputting invoices,” “aggregating attendance data,” and “creating estimates.”

Why? AI agents do not operate on vague commands like “do all accounting tasks.” They require specific tasks like “read this invoice PDF and input it into freee in this format.” Inventorying tasks is the process of creating a blueprint for automation.

This itself incurs no cost. Two to three internal meetings are sufficient. However, if you implement AI agents without this inventory, you will not see any benefits.

2. Test with One Workflow First

Do not attempt to automate all tasks at once. Start with one, the most routine and frequently occurring workflow.

Recommended options are “invoice processing” or “daily report aggregation.” Both have clear rules, few exceptions, and measurable effects. After a month of testing, evaluate how many hours were saved compared to when humans were doing the tasks, the error rate, and the costs involved.

3. Redefine “What Humans Should Do”

When AI agents take over routine tasks, what should humans focus on? If this is not considered, you may end up in a situation where “AI was implemented, but now we have too many people.”

The answer is clear. Judgment, negotiation, relationship building — concentrate human resources on tasks that AI cannot perform. If an accountant is freed from inputting invoices, they can spend time analyzing cash flow or negotiating terms with suppliers. If a sales clerk is relieved from creating estimates, they can enhance the quality of customer interactions.

It is not about “reducing people” but about “enhancing the quality of human work.” This is the essence of “hiring systems.”

From Fixed Costs to Variable Costs — The Structure of SMEs is Changing

The biggest burden on SME management is fixed costs. Labor costs, rent, and lease fees. These do not decrease even when sales drop.

AI agent OS transforms part of labor costs into variable costs. They operate only when busy, and the cost is zero when idle. In a world where each task costs 0.005 yen, processing 10,000 tasks a month would only cost 50 yen.

Of course, we are not yet in an environment where everything runs this smoothly. There are challenges such as tool maturity, Japanese language support, and business-specific customizations. However, the direction is clear.

“Not being able to hire people is preventing growth” — this constraint is on the verge of being lifted by the power of systems.

SMEs stand to benefit the most from this transformation. Large corporations already have excess personnel. SMEs are short-staffed. The impact of compensating for this shortage with systems is significant.

Start by inventorying your tasks. Test with one workflow. Redefine human work. If you begin with these three steps, the landscape you see in six months should be different.