QommonsAI Equipped with 'Deep Research' Feature. Even Integrates with Administrative Knowledge - Entering an Era Where Entire Research Tasks, From Search Planning to Cited Report Generation, Are Automated
Polimill Inc. announced the launch of a new feature, 'Deep Research,' for its generative AI for government, 'QommonsAI,' scheduled for April 1, 2026. This feature automates complex research tasks for local governments by having the AI autonomously conduct searches and generate cited reports.
📋 Article Processing Timeline
- 📰 Published: April 1, 2026 at 07:15
- 🔍 Collected: April 1, 2026 at 01:00
- 🤖 AI Analyzed: April 23, 2026 at 08:30 (535h 29m after Collected)
Polimill Inc. (Headquarters: Minato-ku, Tokyo, Representative Directors: Ayame Ito / Nonoka Taniguchi), a leader in the social implementation of generative AI, has announced that it will begin offering a new feature, 'Deep Research,' in an update scheduled for April 1, 2026, for its generative AI for government, 'QommonsAI'.
■ Towards an Era Where 'Research' is Entrusted to AI
In the policy-making and preparation of assembly responses by local governments, advanced research tasks that involve collecting, organizing, and comparing information across multiple sources are essential. However, in reality, these tasks continue to consume a significant amount of staff time and effort.
'Where should I look?' 'Is the information sufficient?' 'Can I provide the evidence?'
Deep Research allows AI to autonomously handle this entire process.
◾️What is Deep Research?
'Deep Research' is a feature where AI autonomously executes the research process based on user instructions and automatically generates a structured report.
It is not just a simple search.
Decomposition of the question → Formulation of a search plan → Web search → Information scrutiny → Re-search → Report generation
By repeating this cycle, it deepens the investigation as many times as necessary until the required information is reached.
It generates cited outputs while enhancing the comprehensiveness and accuracy of the information.
■ Examples of Automatically Generated Outputs
Because the information source is explicitly stated for all outputs, it fulfills accountability based on evidence.
Cited research memos - Information organization that clearly states the basis
Comparison tables organizing multiple pieces of information - Suitable for comparing other municipal cases and systems
Organized materials by issue - Utilized for preparing assembly responses and explanatory materials
■ Integration with Administrative Knowledge Changes the Depth of Research
QommonsAI's Deep Research is not limited to information on the Web.
It can be used in combination with QommonsAI's cross-search of administrative knowledge from local governments nationwide, or a dedicated RAG (Retrieval-Augmented Generation) storing internal government documents.
In addition to general public information, research and analysis including administrative-specific knowledge such as 'how similar policies were discussed in neighboring municipal assemblies' and 'what are the examples of ordinance enactment in other prefectures' can be completed on a single screen.
◾️Utilization in Local Government Operations
In local government operations, collecting, organizing, and comparing diverse information is required in system design and policy consideration.
Deep Research automates this entire research process, thereby supporting evidence-based decision-making along with improving operational efficiency.
In-depth research of priority projects - Comprehensive comparison and organization of policy options
Preparation of assembly responses - Rapid collection of other municipal cases and evidence
Creation of explanatory materials - Automatic generation of issue organization and cited evidence materials
System design and policy making - Cross-referencing multiple information sources
■ Towards an Era Where 'Research' is Entrusted to AI
In the policy-making and preparation of assembly responses by local governments, advanced research tasks that involve collecting, organizing, and comparing information across multiple sources are essential. However, in reality, these tasks continue to consume a significant amount of staff time and effort.
'Where should I look?' 'Is the information sufficient?' 'Can I provide the evidence?'
Deep Research allows AI to autonomously handle this entire process.
◾️What is Deep Research?
'Deep Research' is a feature where AI autonomously executes the research process based on user instructions and automatically generates a structured report.
It is not just a simple search.
Decomposition of the question → Formulation of a search plan → Web search → Information scrutiny → Re-search → Report generation
By repeating this cycle, it deepens the investigation as many times as necessary until the required information is reached.
It generates cited outputs while enhancing the comprehensiveness and accuracy of the information.
■ Examples of Automatically Generated Outputs
Because the information source is explicitly stated for all outputs, it fulfills accountability based on evidence.
Cited research memos - Information organization that clearly states the basis
Comparison tables organizing multiple pieces of information - Suitable for comparing other municipal cases and systems
Organized materials by issue - Utilized for preparing assembly responses and explanatory materials
■ Integration with Administrative Knowledge Changes the Depth of Research
QommonsAI's Deep Research is not limited to information on the Web.
It can be used in combination with QommonsAI's cross-search of administrative knowledge from local governments nationwide, or a dedicated RAG (Retrieval-Augmented Generation) storing internal government documents.
In addition to general public information, research and analysis including administrative-specific knowledge such as 'how similar policies were discussed in neighboring municipal assemblies' and 'what are the examples of ordinance enactment in other prefectures' can be completed on a single screen.
◾️Utilization in Local Government Operations
In local government operations, collecting, organizing, and comparing diverse information is required in system design and policy consideration.
Deep Research automates this entire research process, thereby supporting evidence-based decision-making along with improving operational efficiency.
In-depth research of priority projects - Comprehensive comparison and organization of policy options
Preparation of assembly responses - Rapid collection of other municipal cases and evidence
Creation of explanatory materials - Automatic generation of issue organization and cited evidence materials
System design and policy making - Cross-referencing multiple information sources