About this webinar 关于本次网络研讨会

Validation teams across life sciences face mounting pressure to reduce cycle times without compromising compliance. This on-demand webinar explores how AI in life sciences validation can accelerate document generation, streamline reviews, and strengthen data integrity — all within a governed, audit-ready framework. Watch to see Kneat’s four-pillar AI strategy in action.

在生命科学领域的验证团队面临着越来越大的压力，需要在不影响合规性的前提下缩短周期时间。这个按需提供的网络研讨会探讨了在生命科学验证中应用人工智能如何能够加速文档生成、简化审核流程，并增强数据完整性——所有这一切都在一个受控且适合审计的框架内完成。请观看 Kneat 公司四重支柱人工智能战略的实际应用案例。

Topics covered 涵盖的主题

• Why governance and data integrity must come before AI deployment in regulated environments

• 在受监管的环境中，为什么治理和数据完整性必须优先于人工智能的部署呢？

• Kneat’s four-pillar AI framework: Generate, Review, Interrogate, and Develop

• Kneat 的四大人工智能框架：生成、审核、询问与开发

• Live walkthrough of the AI Review Assistant for test execution documents

• 人工智能评审辅助工具的实时操作演示，用于测试执行文档的审核工作。

• AI-assisted validation authoring and project builder agent concepts

• 基于人工智能辅助的验证、创作功能，以及项目构建代理概念

• Natural-language querying of validation data and conversational BI

• 对验证数据进行的自然语言查询以及交互式商业智能功能

• Data privacy architecture: foundation models, customer data isolation, and human-in-the-loop controls

• 数据隐私架构：基础模型、客户数据的隔离处理，以及人工干预机制

• Released capabilities versus planned roadmap items through 2027

• 已发布的功能与截至 2027 年的计划路线图项目

• Audience poll results on AI adoption trends among validation professionals

• 关于验证专业人士在人工智能应用趋势方面的民意调查结果

Frequently Asked Questions  常见问题解答

How does Kneat use AI in validation without compromising data integrity?

Kneat 在验证过程中是如何使用人工智能的，而不会损害数据的完整性呢？

Kneat implements AI as an augmentation layer rather than a replacement for human expertise. Every AI feature follows a human-in-the-loop principle, meaning SMEs review and approve all AI-generated suggestions. Kneat uses foundation models and does not train AI on customer data, ensuring all information remains secured within AWS-hosted environments.

Kneat 将人工智能作为辅助工具来使用，而不是取代人类的专业知识。所有的 AI 功能都遵循“人类参与流程”的原则，也就是说，客户专家会审核并批准所有由 AI 生成的建议。Kneat 使用基础模型，不会在客户数据上进行 AI 训练，这样可以确保所有信息都在 AWS 托管的环境中得到保护。

What does the AI Review Assistant actually check?

人工智能审核助手究竟会检查哪些内容呢？

The AI Review Assistant analyzes test execution documents for blank or incomplete fields, logical mismatches between expected and actual results, missing evidence such as required screenshots, and data inaccuracies. It can also use OCR combined with language model reasoning to verify that screenshot content aligns with typed test results. Importantly, the assistant currently reviews one document at a time and its findings are advisory — it does not block approvals.

AI 评审助手能够分析测试执行文档中的空白或不完整字段、预期结果与实际结果之间的逻辑一致性、缺失的证据（如必要的截图）以及数据准确性问题。该工具还可以结合 OCR 技术和语言模型推理，来验证截图内容是否与输入的测试结果一致。重要的是，目前该助手每次只审查一份文档，其发现仅供参考，不会阻碍审批流程的进行。

What AI capabilities are available now in Kneat Gx?

Kneat Gx 目前提供了哪些人工智能功能？

Kneat has already released in-app chat for platform navigation, Data API support for enterprise analytics, AI-translated UI for global usability, and the AI Review Assistant. Upcoming releases include validation summary report generation and AI-driven content authoring for validation documents and protocols.

Kneat 已经推出了以下功能：应用内聊天功能，用于导航；数据 API 支持，便于企业进行数据分析；人工智能驱动的用户界面设计，以提升全球用户的可用性；还有人工智能评审助手工具。即将推出的功能包括生成验证报告，以及利用人工智能技术来编写验证文档和方案的内容。

What is on Kneat's AI roadmap for 2026 and 2027?

Kneat 在 2026 年和 2027 年的 AI 发展路线图是什么？

The roadmap includes an AI Summary Assistant for generating validation summary reports, an AI Validation Expert for answering regulatory questions with source references, and an AI Author Assistant for creating new validation content from approved templates and inputs. Longer-term plans cover risk scoring, conversational BI, broader document review capabilities, a virtual inspection agent, and proactive compliance analytics.

该路线图包括一项人工智能摘要辅助工具，用于生成验证报告；一项人工智能验证专家工具，能够根据来源文档回答监管问题；以及一项人工智能作者辅助工具，能够根据已批准的模板和输入内容创建新的验证内容。从长远来看，还计划开发风险评分功能、对话式商业智能系统、更强大的文档审核能力、虚拟检查代理，以及主动式的合规分析工具。

Can AI in Kneat Gx cross-reference multiple validation documents?

在 Kneat Gx 中，人工智能能否交叉引用多个验证文档呢？

Currently, the AI Review Assistant reviews one document at a time and does not cross-check across specification documents versus protocols. Kneat shared that broader cross-document review capabilities are part of the longer-term roadmap extending into 2027.

目前，AI 审核助手一次只能审核一份文档，不会与各种规范文档或方案进行交叉审核。Kneat 指出，更广泛的文档交叉审核功能属于长期规划的一部分，计划持续到 2027 年。

Does Kneat's AI approach work for different validation use cases like C&Q or CSV?

Kneat 的 AI 方法是否适用于其他验证场景，比如 C&Q 或 CSV 类型的数据处理？

Kneat’s four-pillar AI framework applies across the full range of validation activities managed on the Kneat Gx platform, from equipment validation and commissioning and qualification to computer system validation and beyond. The AI capabilities are designed to support any validation process within the platform’s compliant, configurable environment.

Kneat 的四大支柱人工智能框架适用于 Kneat Gx 平台上所有类型的验证活动，包括设备验证、调试与确认，以及计算机化系统的验证等。该人工智能功能旨在支持平台兼容、可配置环境中的任何验证过程。

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