Logly Launches 'Uruteq MCP Alpha' Enabling AI Agents to Utilize Corporate and Intent Data

Logly, Inc. (Headquarters: Shibuya-ku, Tokyo, Representative Director: Hirokazu Yoshinaga, Securities Code: 6579, hereinafter 'Logly'), provider of the B2B marketing agent 'Uruteq' (https://uruteq.logly.co.jp/), began offering 'Uruteq MCP Alpha' on Wednesday, May 20, 2026. This new feature allows AI agents such as Claude and ChatGPT to reference and utilize corporate data, CV (conversion) information like document requests and inquiries, and intent data accumulated on Uruteq.

With this feature, users can classify site-visiting companies, extract promising sales targets, create individualized contact messages, draft approach messages via inquiry forms, analyze advertisements, and design content—all through AI agents.

■ Development Background

While the use of generative AI is expanding into data analysis and business support, B2B marketing professionals face challenges in practically utilizing scattered customer data (site visits, CVs, intent information, etc.). Previously, users had to check data with tools and then manually perform company research, CRM cross-referencing, and creation of sales lists and individual messages, resulting in a significant daily workload.

■ What is Uruteq MCP Alpha?

'Uruteq MCP Alpha' is a feature that enables AI agents like Claude and ChatGPT to reference and utilize the corporate data, behavioral data, and intent data accumulated in Uruteq.

This allows representatives not only to view data on the Uruteq management screen but also to give instructions to AI agents, such as 'Classify companies that recently viewed the pricing page,' 'Extract non-CV companies that exhibit similar behavior to CV companies,' or 'Create a contact message for high-priority sales target companies.'

■ Features of Uruteq MCP Alpha

1. AI agents reference and utilize proprietary B2B data

Users can call upon company-specific data from external AI agents, including information on site-visiting companies, filtering lists, access data such as site browsing time, sessions, and referrers, as well as CV information and intent keywords.

2. Realizing the shift from 'looking at data' to 'creating the next action'

Practical outputs such as extracting lists of promising companies, classifying sales priorities, and creating draft individual emails and approach messages via inquiry forms can be executed on the AI.

3. Unearthing 'promising companies before CV'

Because it can acquire and utilize not only CV data but also pre-CV site-visiting companies and intent information, it is possible to create approach hypotheses for promising companies that have not yet made an inquiry.

■ Specific Use Cases

Data integration through this feature enables actions directly linked to practical business, such as:

- Generation and sending of personalized emails via CRM integration
Triggered by Slack or email notifications, the system automatically connects to platforms like HubSpot to auto-generate and send personalized emails tailored to customer needs.

- Automation of form approaches to uncontacted companies
By linking Uruteq data with existing CRM/MA, it extracts only new companies and automatically sends automated form sales messages with text generated specifically for each company.

- Design of original content plans based on proprietary data
By analyzing the session information of CV users, it is possible to design unique content plans that deeply resonate with target customers without relying on the general knowledge of AI (generic data).

- Interdepartmental collaboration combining meeting minutes and intent data
Automatically combining negotiation minutes with Uruteq's intent data improves customer resolution and enables operations with strong collaboration between sales and marketing.

■ Target Users

Limited to companies that have contracted Uruteq.

The target audience includes B2B marketing representatives, as well as sales and inside sales representatives.

By utilizing this feature, the goal is to significantly reduce the man-hours required for checking, organizing, and drafting texts for sales preparation. In our internal verification, we confirmed the potential to reduce sales preparation, which took about 1 hour every morning, to about 5 minutes. Additionally, it becomes easier to consider approaches tailored to the interests and consideration status of each company.

■ Future Outlook

As an alpha version, this feature will initially be provided only to companies that have contracted 'Uruteq'. We will proceed with verification and utilization in actual sales and marketing operations. In the future, we plan to expand it to strengthen integration with MA and CRMs, including HubSpot, to more smoothly handle everything from checking contact status to sales notifications.

■ Comment from the Business Manager (Shota Inoue, Uruteq Business Manager)

Bto...