Defining Requirements with AI: ZenTech Launches Closed Beta of 'DefineAI'
On May 11, 2026, ZenTech launched the closed beta for 'DefineAI', an AI service for requirement definition. By automating requirement generation, reviews, and mockup creation, the service aims to improve upstream quality and reduce rework.
📋 Article Processing Timeline
- 📰 Published: May 25, 2026 at 21:00
- 🔍 Collected: May 25, 2026 at 12:31
- 🤖 AI Analyzed: May 25, 2026 at 12:40 (9 min after Collected)
ZenTech, based in Shibuya, Tokyo, and led by CEO Akira Sakai, announced on May 11, 2026, the launch of the closed beta for its requirement definition AI service, 'DefineAI'.
DefineAI is a platform designed to enhance the efficiency and quality of requirement definition through features such as automated requirement generation, AI-powered reviews, automatic screen mockup generation, and meeting minutes compilation.
As the adoption of generative and coding AI grows, the importance of accurately defining 'what to build' and 'why' has become increasingly critical in development environments. ZenTech introduces DefineAI as a foundational layer for upstream engineering to support development quality in the AI era.
## Background: In the Era of Coding AI, Rework Stems from 'Ambiguous Requirements'
While generative AI is significantly accelerating coding speeds, rework in development projects often stems not from implementation speed itself, but from ambiguous requirements, scattered documentation, misunderstandings among stakeholders, and a lack of acceptance criteria.
Poor quality or missing definitions in the requirements phase often lead to discovered deficiencies later in the process, resulting in project delays and budget overruns. DefineAI was developed to solve this by standardizing requirements definition and providing AI support as a structural mechanism.
## About DefineAI
DefineAI standardizes the requirements definition process (templating). For example, teams can establish internal standards for specific project types (e.g., e-commerce systems), ensuring consistent quality regardless of who performs the definition work.
## Problems DefineAI Solves
- Inconsistent quality in requirements definition
- Over-reliance on individual expertise
- Shortage of skilled requirement analysts
- Rework caused by ambiguous requirements progressing to development
- Unstable output from coding AI due to unclear prerequisite requirements
## Key Features
1. Requirement Cards: Structuring requirements to eliminate ambiguity.
2. AI Review: Providing AI feedback on omissions, ambiguity, and contradictions.
3. Mockup Generation: Early visualization to align stakeholders.
4. AI Chat: Assisting in generating cards and refining project requirements.
5. Enterprise-Ready Architecture: Supports air-gapped networks, self-hosting, and auditability.
## Statement from CEO
'DefineAI is not intended to replace PMs or SEs. At this stage, requirements should be defined by humans, and DefineAI acts as an upstream infrastructure to support system development in the AI era,' said Akira Sakai, CEO of ZenTech.
DefineAI is a platform designed to enhance the efficiency and quality of requirement definition through features such as automated requirement generation, AI-powered reviews, automatic screen mockup generation, and meeting minutes compilation.
As the adoption of generative and coding AI grows, the importance of accurately defining 'what to build' and 'why' has become increasingly critical in development environments. ZenTech introduces DefineAI as a foundational layer for upstream engineering to support development quality in the AI era.
## Background: In the Era of Coding AI, Rework Stems from 'Ambiguous Requirements'
While generative AI is significantly accelerating coding speeds, rework in development projects often stems not from implementation speed itself, but from ambiguous requirements, scattered documentation, misunderstandings among stakeholders, and a lack of acceptance criteria.
Poor quality or missing definitions in the requirements phase often lead to discovered deficiencies later in the process, resulting in project delays and budget overruns. DefineAI was developed to solve this by standardizing requirements definition and providing AI support as a structural mechanism.
## About DefineAI
DefineAI standardizes the requirements definition process (templating). For example, teams can establish internal standards for specific project types (e.g., e-commerce systems), ensuring consistent quality regardless of who performs the definition work.
## Problems DefineAI Solves
- Inconsistent quality in requirements definition
- Over-reliance on individual expertise
- Shortage of skilled requirement analysts
- Rework caused by ambiguous requirements progressing to development
- Unstable output from coding AI due to unclear prerequisite requirements
## Key Features
1. Requirement Cards: Structuring requirements to eliminate ambiguity.
2. AI Review: Providing AI feedback on omissions, ambiguity, and contradictions.
3. Mockup Generation: Early visualization to align stakeholders.
4. AI Chat: Assisting in generating cards and refining project requirements.
5. Enterprise-Ready Architecture: Supports air-gapped networks, self-hosting, and auditability.
## Statement from CEO
'DefineAI is not intended to replace PMs or SEs. At this stage, requirements should be defined by humans, and DefineAI acts as an upstream infrastructure to support system development in the AI era,' said Akira Sakai, CEO of ZenTech.
FAQ
DefineAIの主な機能は何ですか?
要件の自動生成、定義内容のAIレビュー、画面モックアップの自動生成、議事録の自動生成、およびエンタープライズ向けの導入設計(閉域ネットワークや監査性対応など)を提供します。
DefineAIはどのような課題を解決しますか?
要件定義の品質バラツキや属人化、人材不足の解消に加え、曖昧な定義に起因する開発後工程での手戻りや、コード生成AIの品質安定化といった課題を解決します。
誰が利用対象ですか?
SIerや事業会社のプロダクトマネージャー(PM)、システムエンジニア(SE)、および要件定義の改善に取り組む企業が対象です。
DefineAIの提供形態は?
現在はClosedβ版として提供を開始しており、実案件での検証を通じて機能改善を進めています。
企業の導入にあたってのセキュリティ面は考慮されていますか?
エンタープライズ前提の導入設計として、閉域ネットワークやセルフホスト、権限管理、監査性、LLM選択の自由度を考慮した設計を支援します。