RightTouch Launches 'Conversation Harness' for AI Self-Improvement and Operational Safety
RightTouch has launched 'Conversation Harness', a feature that automatically improves the operational quality of AI operators and prevents hallucinations.
📋 Article Processing Timeline
- 📰 Published: May 26, 2026 at 19:00
- 🔍 Collected: May 26, 2026 at 10:31
- 🤖 AI Analyzed: May 26, 2026 at 23:38 (13h 6m after Collected)
## Overview
RightTouch (Headquarters: Shinagawa-ku, Tokyo; CEOs: Shuhei Nomura / Daito Nagasaki), a provider of AI contact center infrastructure for enterprises, has announced the launch of 'Conversation Harness,' a new feature for the QANT AI operator that enables operational quality self-improvement and ensures safety.
Conversation Harness serves as a foundation for continuously enhancing the quality of AI operator operations without relying solely on manual labor. The AI automatically analyzes response logs, automating everything from issue detection to the creation, validation, and implementation of improvement proposals, thereby accelerating the knowledge self-improvement cycle. By designing the system so that humans only handle final decisions on implementing improvements, the system achieves both reduced operational workload and quality assurance.
Furthermore, as a final risk hedge against critical accidents during interactions—such as hallucinations—the system is equipped with multi-layered guardrail functionality.
By functioning through both the 'self-improvement cycle' and 'multi-layered guardrails,' the quality of the AI operator improves the more it is operated, while critical accidents are intercepted.
## Background of Development
While the adoption of generative AI in contact centers is spreading rapidly, maintaining operational quality has become a challenge. Massive daily tasks—such as visual inspection of AI operator logs, continuous adjustments to prompts, and knowledge updates—make it structurally difficult to keep up with manual labor alone.
Furthermore, there is the risk of hallucinations inherent to generative AI. Conversation Harness addresses these issues by combining an automated self-improvement cycle with real-time multi-layered guardrails.
## Components of Conversation Harness
- Post-interaction self-improvement cycle (Offensive): Analyzes interaction logs to continuously improve knowledge and prompts.
- Multi-layered guardrails during interaction (Defensive): Instantly blocks critical accidents such as hallucinations.
RightTouch (Headquarters: Shinagawa-ku, Tokyo; CEOs: Shuhei Nomura / Daito Nagasaki), a provider of AI contact center infrastructure for enterprises, has announced the launch of 'Conversation Harness,' a new feature for the QANT AI operator that enables operational quality self-improvement and ensures safety.
Conversation Harness serves as a foundation for continuously enhancing the quality of AI operator operations without relying solely on manual labor. The AI automatically analyzes response logs, automating everything from issue detection to the creation, validation, and implementation of improvement proposals, thereby accelerating the knowledge self-improvement cycle. By designing the system so that humans only handle final decisions on implementing improvements, the system achieves both reduced operational workload and quality assurance.
Furthermore, as a final risk hedge against critical accidents during interactions—such as hallucinations—the system is equipped with multi-layered guardrail functionality.
By functioning through both the 'self-improvement cycle' and 'multi-layered guardrails,' the quality of the AI operator improves the more it is operated, while critical accidents are intercepted.
## Background of Development
While the adoption of generative AI in contact centers is spreading rapidly, maintaining operational quality has become a challenge. Massive daily tasks—such as visual inspection of AI operator logs, continuous adjustments to prompts, and knowledge updates—make it structurally difficult to keep up with manual labor alone.
Furthermore, there is the risk of hallucinations inherent to generative AI. Conversation Harness addresses these issues by combining an automated self-improvement cycle with real-time multi-layered guardrails.
## Components of Conversation Harness
- Post-interaction self-improvement cycle (Offensive): Analyzes interaction logs to continuously improve knowledge and prompts.
- Multi-layered guardrails during interaction (Defensive): Instantly blocks critical accidents such as hallucinations.
FAQ
Conversation Harnessとはどのような機能ですか？
AIオペレーターの運用品質を自動で高め、ハルシネーション等の致命的な事故を防ぐためのガードレール機能を備えた基盤です。
Conversation Harnessの自己改善サイクルはどのように機能しますか？
AIが応対ログを評価し、ナレッジやプロンプトの課題を自動的に抽出・分類・改善することで、運用品質を継続的に向上させます。
AIオペレーターにおけるハルシネーション対策はありますか？
応対中にハルシネーション等をリアルタイムで監視し、即時に誤案内を遮断する多層的なガードレール機能を搭載しています。
この機能導入による運用上のメリットは何ですか？
改善反映の最終判断のみを人間が担うことで運用負荷を削減しつつ、AIの品質保証と安全性を両立できます。
RightTouchが提供するソリューションの主な対象は何ですか？
エンタープライズ向けのAIコンタクトセンター基盤です。