Japanese tech firm Kintone launches free AI no-code builder

Japanese tech firm Kintone launches free AI no-code builder

Tech in Asia·2025-08-19 11:00

Kintone, a Tokyo-based digital workplace platform and subsidiary of Cybozu, has launched Kintone AI Lab, a free beta service to help businesses build AI-powered apps without coding.

The feature lets users create apps and set up workflow processes through conversational chat commands within the Kintone platform.

The service targets small and medium-sized businesses facing high software costs and limited IT resources.

Initial features include an AI App Creator that suggests app structures from user descriptions and an AI Process Creator to automate workflow tasks.

Kintone AI Lab is built with enterprise-level security, including permission controls and data privacy protections that prevent user data from being used to train external AI models.

The free beta is available to existing customers in the United States, Southeast Asia, and Oceania starting August 19, 2025.

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🔗 Source: Kintone

🧠 Food for thought

1️⃣ No-code platforms dramatically reduce software development costs for small businesses

Kintone’s AI Lab launch highlights how no-code solutions address a significant cost gap in business software development.

Custom software development typically costs between $75,000 to $750,000, while no-code platforms like Kintone start at $24 per user per month1.

This represents a potential cost reduction for small businesses that previously couldn’t afford custom solutions.

For example, a 10-person team using Kintone would pay $2,880 annually versus potentially hundreds of thousands for custom development.

This cost advantage allows businesses to “start small, achieve quick wins, and scale their digital transformation at a sustainable pace,” as Kintone describes their approach.

2️⃣ Conversational AI interfaces remove the last technical barrier for business users

The chat-based interface in Kintone AI Lab represents the evolution from visual drag-and-drop builders to natural language commands.

SMBs have historically struggled with AI implementation due to talent shortages and technical complexity, making conversational interfaces particularly valuable2.

Instead of learning interface conventions or workflow logic, users can simply describe business problems like “I need an app to track customer inquiries” and receive functional applications.

This approach addresses SMBs’ core frustration: the belief that custom software is “too expensive, too complicated, and requiring developers they can’t find or afford.”

The timing aligns with broader no-code AI adoption, where tools now provide access to AI capabilities that previously required technical expertise3.

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