Kaizen Platform Launches 'KAIZEN ENGINE for Extension,' a Chrome-based AI Integration Platform for Existing Systems

Kaizen Platform (Headquarters: Minato-ku, Tokyo; CEO: Kenji Sudo) has launched 'KAIZEN ENGINE for Extension,' a service enabling AI use on business screens through Chrome extension side panels without altering legacy core systems or SaaS platforms. Several companies have already begun early implementation.

Building on its experience supporting over 1,400 companies in website UX improvement with its 'KAIZEN ENGINE' technology, the company is now expanding its philosophy to Employee Experience (EX). The new service accumulates and analyzes operation logs (EX logs), enabling businesses to accelerate the PDCA cycle for AI-driven improvements.

Background: Non-modifiable systems are a bottleneck for AI utilization Due to declining labor populations and increasing workloads, securing human resources has become challenging, making Generative AI a business necessity. However, core business systems and SaaS often present structural constraints—such as high modification costs or third-party ownership—that prevent AI integration, leaving employees with manual tasks like copy-pasting, screen-switching, and visual checking.

Since its founding, Kaizen Platform has provided 'KAIZEN ENGINE,' which enables UX implementation and improvement by adding a single tag to websites. However, business systems and SaaS do not allow tag injection. To overcome this, the company developed 'KAIZEN ENGINE for Extension,' which attaches AI to the Chrome browser that employees use daily.

Key Features of 'KAIZEN ENGINE for Extension' - AI business improvement without modifying existing systems Using the side panel of a Chrome extension, it enables AI capabilities such as information reading, summarization, judgment, text generation, and screen operation assistance without modifying the existing system. It also comes standard with member management, usage reporting, and a RAG (Retrieval-Augmented Generation) infrastructure that references internal documents.

- Visualization of business lead times via EX logs Like web access analytics, operations and AI usage are accumulated as logs. This allows for quantitative tracking of time per process and continuous improvement by measuring productivity before and after interventions.

- 'A/B Testing' for business operations Similar to website improvements, companies can test multiple operational workflows in parallel and use EX logs to verify which yields higher productivity. By incorporating successful methods into AI workflows, the tacit knowledge of high performers can be established as an organizational standard.

Use Cases Sales support (analysis of CRM data, email generation), review screening, call center/office support, indirect department assistance (quote generation, document creation), requirement definition for system development, and job-matching/scout generation for recruiting.

Implementation Implementation can start in about 1-1.5 months after defining target operations and screens, followed by a 3-month program to build new operational standards based on EX logs and A/B tests.

Future Outlook Kaizen Platform aims to integrate its data processing and execution infrastructure ('KAIZEN ENGINE' and 'Kaizen AI Cloud') across web channels, business systems, and other communication channels. By handling both UX and EX data on a unified platform and deploying Forward Deployed Engineers (FDEs) on-site, the company intends to transition manual operational tasks to AI, continuing to evolve its business as a platform that drives both marketing and operations with AI.