CINC Launches Infrastructure for Service Delivery Leveraging Expert Knowledge and AI Agents

CINC (Headquarters: Minato-ku, Tokyo; President: Tomonori Ishimatsu) has announced the start of the 'Knowledge Engineering Project,' designed to organize and implement accumulated research methodologies, proposal know-how, and operational insights as reusable knowledge assets through AI.

In this project, CINC aims to move beyond merely archiving the implicit knowledge of experienced team members. By refining this knowledge into a format usable in practical work, the company intends to build a system that minimizes variability in response quality across projects, while delivering value to customers faster and with greater precision.

<Background> To convert generative AI and AI agent initiatives into results, it is essential to organize and utilize knowledge as an organization. Rather than keeping knowledge within individuals, building, deploying, and permeating it organizationally allows for greater achievements and the accumulation of these insights as assets.

Looking toward a transformation into an AI-first business, CINC has begun building a foundation to convert internal insights from 'experience-based rules known only to individuals' into 'knowledge assets usable by the organization' in combination with AI.

<Project Overview> This project focuses on using generative AI 'skills' to realize the AI agentization of business operations. Skills are bundles of work procedures and decision-making criteria passed to AI. Based on this, the company will collect and organize frontline insights and structure them into a format that is easily reproducible even for tasks previously dependent on individual experience.

The main initiatives are as follows:

1. Building an AI Agent Usage Environment Positioning AI agents as essential intellectual assets, the company will build a secure and convenient usage environment.

2. AI Agentization of Knowledge Organizing internal knowledge into 'skills' that AI agents can use in practical operations. Simultaneously, the company will establish flow management for knowledge creation, approval, and deployment, and form a 'Knowledge Engineering Team' centered around the AI Strategy Department.

3. Development of Data Infrastructure for AI Agents Developing APIs and MCPs required for AI agents, while establishing systems to acquire, accumulate, and manage the context needed for knowledge utilization.

4. Harness Development for AI Agent Utilization Building a design and operational foundation, including context design, constraint and guardrail implementation, AI-based evaluation and improvement loops, and approval/audit flows to ensure governance.

Through these efforts, CINC expects to achieve the following effects: - Stabilization of proposal quality - Improvement in response speed - Inheritance of know-how - Improvement in reproducibility

CINC will continue to contribute to resolving customer issues by linking knowledge not just to accumulation, but to actual business operations and AI utilization.