Ask Dona: An AI platform for Enterprise
BATCH ANALYSIS
BATCH ANALYSIS
Powered by AskDona’s core technology dona-rag-2.0, AskDona Batch dramatically streamlines labor-intensive organizational work by automating large volumes of pre-defined questions and lists — all at once.
Powered by AskDona’s core technology dona-rag-2.0, AskDona Batch dramatically streamlines labor-intensive organizational work by automating large volumes of pre-defined questions and lists — all at once.
Powered by AskDona’s core technology dona-rag-2.0, AskDona Batch dramatically streamlines labor-intensive organizational work by automating large volumes of pre-defined questions and lists — all at once.
Higher accuracy,
faster first-level assessment —
powered by AI agents.
Batch Assessment automatically evaluates predefined assessment items and classifies each as “Compliant,” “Not compliant,” or “Not applicable,” based on verified knowledge stored in AskDona. It extends the same automation benefits of Batch Process — beyond answer drafting — into the actual assessment workflow.
AI-powered objective, high-accuracy automated decision-making
AskDona supports Excel files (.xlsx/.xls) as well as Word, PowerPoint, PDF, and many other formats. Simply upload internal documents such as security policies or product manuals — AskDona will organize them into a searchable knowledge base automatically.
For more information about dona-rag-2.0
The AI agent applies evaluation criteria defined by administrators and references evidence retrieved using dona-rag-2.0’s high-precision search capabilities. This ensures consistent, objective assessments — eliminating human interpretation gaps and reducing evaluation variance across reviewers.
A highly transparent decision process based on documented evidence
Each AI judgment clearly shows:
• The reasoning behind the decision
• The exact supporting evidence and document sources
Users can verify every determination, confirm validity, and make final approval with confidence.
A new decision category, “Undeterminable,” to indicate insufficient evidence
If relevant information does not exist in the RAG database, the AI will return results such as “Insufficient information” or “Unable to determine.”
This makes missing documentation visible and encourages ongoing knowledge enhancement for better future assessments.
Case Study: JSOL
~2,000 hours of system risk assessment workload reduced per year
JSOL, a member of the NTT DATA and SMBC Group, uses AskDona Batch Assessment to support risk assessments across more than 100 systems and 400 evaluation items.
Results:
• Over 90% consistency between AI classification and human reviewers
• ~45% reduction in manual workload per system
• An expected annual reduction of ~2,000 work hours (~260 person-days)
This case demonstrates how AskDona enables standardization and efficiency in governance and compliance workflows.
👉 Read the full press release from JSOL & GFLOPS
Batch Assessment
Batch Process
Higher accuracy,
faster first-level assessment —
powered by AI agents.
Batch Assessment automatically evaluates predefined assessment items and classifies each as “Compliant,” “Not compliant,” or “Not applicable,” based on verified knowledge stored in AskDona. It extends the same automation benefits of Batch Process — beyond answer drafting — into the actual assessment workflow.
AI-powered objective, high-accuracy automated decision-making
AskDona supports Excel files (.xlsx/.xls) as well as Word, PowerPoint, PDF, and many other formats. Simply upload internal documents such as security policies or product manuals — AskDona will organize them into a searchable knowledge base automatically.
For more information about dona-rag-2.0
The AI agent applies evaluation criteria defined by administrators and references evidence retrieved using dona-rag-2.0’s high-precision search capabilities. This ensures consistent, objective assessments — eliminating human interpretation gaps and reducing evaluation variance across reviewers.
A highly transparent decision process based on documented evidence
Each AI judgment clearly shows:
• The reasoning behind the decision
• The exact supporting evidence and document sources
Users can verify every determination, confirm validity, and make final approval with confidence.
A new decision category, “Undeterminable,” to indicate insufficient evidence
If relevant information does not exist in the RAG database, the AI will return results such as “Insufficient information” or “Unable to determine.”
This makes missing documentation visible and encourages ongoing knowledge enhancement for better future assessments.
Case Study: JSOL
~2,000 hours of system risk assessment workload reduced per year
JSOL, a member of the NTT DATA and SMBC Group, uses AskDona Batch Assessment to support risk assessments across more than 100 systems and 400 evaluation items.
Results:
• Over 90% consistency between AI classification and human reviewers
• ~45% reduction in manual workload per system
• An expected annual reduction of ~2,000 work hours (~260 person-days)
This case demonstrates how AskDona enables standardization and efficiency in governance and compliance workflows.
👉 Read the full press release from JSOL & GFLOPS
Batch Assessment
Batch Process
Higher accuracy, faster first-level assessment — powered by AI agents.
Batch Assessment automatically evaluates predefined assessment items and classifies each as “Compliant,” “Not compliant,” or “Not applicable,” based on verified knowledge stored in AskDona. It extends the same automation benefits of Batch Process — beyond answer drafting — into the actual assessment workflow.
AI-powered objective, high-accuracy automated decision-making
AskDona supports Excel files (.xlsx/.xls) as well as Word, PowerPoint, PDF, and many other formats.
Simply upload internal documents such as security policies or product manuals — AskDona will organize them into a searchable knowledge base automatically.
For more information about dona-rag-2.0
The AI agent applies evaluation criteria defined by administrators and references evidence retrieved using dona-rag-2.0’s high-precision search capabilities.
This ensures consistent, objective assessments — eliminating human interpretation gaps and reducing evaluation variance across reviewers.
A highly transparent decision process based on documented evidence
Each AI judgment clearly shows:
• The reasoning behind the decision
• The exact supporting evidence and document sources
Users can verify every determination, confirm validity, and make final approval with confidence.
Each AI judgment clearly shows:
• The reasoning behind the decision
• The exact supporting evidence and document sources
Users can verify every determination, confirm validity, and make final approval with confidence.
A new decision category, “Undeterminable,” to indicate insufficient evidence
If relevant information does not exist in the RAG database, the AI will return results such as “Insufficient information” or “Unable to determine.”
This makes missing documentation visible and encourages ongoing knowledge enhancement for better future assessments.
If relevant information does not exist in the RAG database, the AI will return results such as “Insufficient information” or “Unable to determine.”
This makes missing documentation visible and encourages ongoing knowledge enhancement for better future assessments.
Batch Assessment
Batch Process
Case Study: JSOL
~2,000 hours of system risk assessment workload reduced per year
JSOL, a member of the NTT DATA and SMBC Group, uses AskDona Batch Assessment to support risk assessments across more than 100 systems and 400 evaluation items.
Results:
• Over 90% consistency between AI classification and human reviewers
• ~45% reduction in manual workload per system
• An expected annual reduction of ~2,000 work hours (~260 person-days)
This case demonstrates how AskDona enables standardization and efficiency in governance and compliance workflows.
👉 Read the full press release from JSOL & GFLOPS
Higher accuracy, faster first-level assessment — powered by AI agents.
Batch Assessment automatically evaluates predefined assessment items and classifies each as “Compliant,” “Not compliant,” or “Not applicable,” based on verified knowledge stored in AskDona. It extends the same automation benefits of Batch Process — beyond answer drafting — into the actual assessment workflow.
AI-powered objective, high-accuracy automated decision-making
AskDona supports Excel files (.xlsx/.xls) as well as Word, PowerPoint, PDF, and many other formats.
Simply upload internal documents such as security policies or product manuals — AskDona will organize them into a searchable knowledge base automatically.
For more information about dona-rag-2.0
The AI agent applies evaluation criteria defined by administrators and references evidence retrieved using dona-rag-2.0’s high-precision search capabilities.
This ensures consistent, objective assessments — eliminating human interpretation gaps and reducing evaluation variance across reviewers.
A highly transparent decision process based on documented evidence
Each AI judgment clearly shows:
• The reasoning behind the decision
• The exact supporting evidence and document sources
Users can verify every determination, confirm validity, and make final approval with confidence.
Each AI judgment clearly shows:
• The reasoning behind the decision
• The exact supporting evidence and document sources
Users can verify every determination, confirm validity, and make final approval with confidence.
A new decision category, “Undeterminable,” to indicate insufficient evidence
If relevant information does not exist in the RAG database, the AI will return results such as “Insufficient information” or “Unable to determine.”
This makes missing documentation visible and encourages ongoing knowledge enhancement for better future assessments.
If relevant information does not exist in the RAG database, the AI will return results such as “Insufficient information” or “Unable to determine.”
This makes missing documentation visible and encourages ongoing knowledge enhancement for better future assessments.
Batch Assessment
Batch Process
Case Study: JSOL
~2,000 hours of system risk assessment workload reduced per year
JSOL, a member of the NTT DATA and SMBC Group, uses AskDona Batch Assessment to support risk assessments across more than 100 systems and 400 evaluation items.
Results:
• Over 90% consistency between AI classification and human reviewers
• ~45% reduction in manual workload per system
• An expected annual reduction of ~2,000 work hours (~260 person-days)
This case demonstrates how AskDona enables standardization and efficiency in governance and compliance workflows.
👉 Read the full press release from JSOL & GFLOPS
Higher accuracy,
faster first-level assessment —
powered by AI agents.
Batch Assessment automatically evaluates predefined assessment items and classifies each as “Compliant,” “Not compliant,” or “Not applicable,” based on verified knowledge stored in AskDona. It extends the same automation benefits of Batch Process — beyond answer drafting — into the actual assessment workflow.
AI-powered objective, high-accuracy automated decision-making.
AskDona supports Excel files (.xlsx/.xls) as well as Word, PowerPoint, PDF, and many other formats. Simply upload internal documents such as security policies or product manuals — AskDona will organize them into a searchable knowledge base automatically.
For more information about dona-rag-2.0
The AI agent applies evaluation criteria defined by administrators and references evidence retrieved using dona-rag-2.0’s high-precision search capabilities.
This ensures consistent, objective assessments — eliminating human interpretation gaps and reducing evaluation variance across reviewers.
A highly transparent decision process based on documented evidence.
Each AI judgment clearly shows:
• The reasoning behind the decision
• The exact supporting evidence and document sources
Users can verify every determination, confirm validity, and make final approval with confidence.
A new decision category, “Undeterminable,” to indicate insufficient evidence.
If relevant information does not exist in the RAG database, the AI will return results such as “Insufficient information” or “Unable to determine.”
This makes missing documentation visible and encourages ongoing knowledge enhancement for better future assessments.
Case Study: JSOL
~2,000 hours of system risk assessment workload reduced per year
JSOL, a member of the NTT DATA and SMBC Group, uses AskDona Batch Assessment to support risk assessments across more than 100 systems and 400 evaluation items.
Results:
• Over 90% consistency between AI classification and human reviewers
• ~45% reduction in manual workload per system
• An expected annual reduction of ~2,000 work hours (~260 person-days)
This case demonstrates how AskDona enables standardization and efficiency in governance and compliance workflows.
👉 Read the full press release from JSOL & GFLOPS
Batch Assessment
Batch Process
Higher accuracy,
faster first-level assessment —
powered by AI agents.
Batch Assessment automatically evaluates predefined assessment items and classifies each as “Compliant,” “Not compliant,” or “Not applicable,” based on verified knowledge stored in AskDona. It extends the same automation benefits of Batch Process — beyond answer drafting — into the actual assessment workflow.
AI-powered objective, high-accuracy automated decision-making.
AskDona supports Excel files (.xlsx/.xls) as well as Word, PowerPoint, PDF, and many other formats. Simply upload internal documents such as security policies or product manuals — AskDona will organize them into a searchable knowledge base automatically.
For more information about dona-rag-2.0
The AI agent applies evaluation criteria defined by administrators and references evidence retrieved using dona-rag-2.0’s high-precision search capabilities.
This ensures consistent, objective assessments — eliminating human interpretation gaps and reducing evaluation variance across reviewers.
A highly transparent decision process based on documented evidence.
Each AI judgment clearly shows:
• The reasoning behind the decision
• The exact supporting evidence and document sources
Users can verify every determination, confirm validity, and make final approval with confidence.
A new decision category, “Undeterminable,” to indicate insufficient evidence.
If relevant information does not exist in the RAG database, the AI will return results such as “Insufficient information” or “Unable to determine.”
This makes missing documentation visible and encourages ongoing knowledge enhancement for better future assessments.
Case Study: JSOL
~2,000 hours of system risk assessment workload reduced per year
JSOL, a member of the NTT DATA and SMBC Group, uses AskDona Batch Assessment to support risk assessments across more than 100 systems and 400 evaluation items.
Results:
• Over 90% consistency between AI classification and human reviewers
• ~45% reduction in manual workload per system
• An expected annual reduction of ~2,000 work hours (~260 person-days)
This case demonstrates how AskDona enables standardization and efficiency in governance and compliance workflows.
👉 Read the full press release from JSOL & GFLOPS
Batch Assessment
Batch Process
Frequently asked questions
Frequently asked questions
Frequently asked questions
Will the data I upload to the RAG database be stored on a domestic server?
Yes, files uploaded to the RAG database are managed on servers within Japan.
Will the data I upload to the RAG database be stored on a domestic server?
Yes, files uploaded to the RAG database are managed on servers within Japan.
Will the data I upload to the RAG database be stored on a domestic server?
Yes, files uploaded to the RAG database are managed on servers within Japan.
Will the data I upload to the RAG database be stored on a domestic server?
Yes, files uploaded to the RAG database are managed on servers within Japan.
Will the data I upload to the RAG database be stored on a domestic server?
Yes, files uploaded to the RAG database are managed on servers within Japan.
Is the AskDona usage environment separated from other companies?
Is the AskDona usage environment separated from other companies?
Is the AskDona usage environment separated from other companies?
Is the AskDona usage environment separated from other companies?
Is the AskDona usage environment separated from other companies?
Can I use AskDona in my own cloud environment?
Can I use AskDona in my own cloud environment?
Can I use AskDona in my own cloud environment?
Can I use AskDona in my own cloud environment?
Can I use AskDona in my own cloud environment?
What are the file formats and capacity limits that can be stored in RAG?
What are the file formats and capacity limits that can be stored in RAG?
What are the file formats and capacity limits that can be stored in RAG?
What are the file formats and capacity limits that can be stored in RAG?
What are the file formats and capacity limits that can be stored in RAG?
Will internal data be used to train ChatGPT?
Will internal data be used to train ChatGPT?
Will internal data be used to train ChatGPT?
Will internal data be used to train ChatGPT?
Will internal data be used to train ChatGPT?
Start with a free consultation.
AskDona is dedicated to Redefining Roles. We empower your organization by assigning all AI-capable tasks to the technology, allowing you to focus on critical human functions and innovation.
Contact us
Contact us
Our RAG model
Our RAG model
Start with a free consultation.
AskDona is dedicated to Redefining Roles. We empower your organization by assigning all AI-capable tasks to the technology, allowing you to focus on critical human functions and innovation.
Contact us
Contact us
Our RAG model
Our RAG model
Start with a free consultation.
AskDona is dedicated to Redefining Roles. We empower your organization by assigning all AI-capable tasks to the technology, allowing you to focus on critical human functions and innovation.
Contact us
Contact us
Our RAG model
Our RAG model
Start with a free consultation.
AskDona is dedicated to Redefining Roles. We empower your organization by assigning all AI-capable tasks to the technology, allowing you to focus on critical human functions and innovation.
Contact us
Contact us
Our RAG model
Our RAG model
Start with a free consultation.
AskDona is dedicated to Redefining Roles. We empower your organization by assigning all AI-capable tasks to the technology, allowing you to focus on critical human functions and innovation.
Contact us
Contact us
Our RAG model
Our RAG model
Higher accuracy, faster first-level
assessment — powered by AI agents.
Batch Assessment automatically evaluates predefined assessment items and classifies each as “Compliant,” “Not compliant,” or “Not applicable,” based on verified knowledge stored in AskDona. It extends the same automation benefits of Batch Process — beyond answer drafting — into the actual assessment workflow.
AI-powered objective, high-accuracy automated decision-making
AskDona supports Excel files (.xlsx/.xls) as well as Word, PowerPoint, PDF, and many other formats.
Simply upload internal documents such as security policies or product manuals — AskDona will organize them into a searchable knowledge base automatically.
For more information about dona-rag-2.0
The AI agent applies evaluation criteria defined by administrators and references evidence retrieved using dona-rag-2.0’s high-precision search capabilities.
This ensures consistent, objective assessments — eliminating human interpretation gaps and reducing evaluation variance across reviewers.
A highly transparent decision process based on documented evidence
Each AI judgment clearly shows:
• The reasoning behind the decision
• The exact supporting evidence and document sources
Users can verify every determination, confirm validity, and make final approval with confidence.
Each AI judgment clearly shows:
• The reasoning behind the decision
• The exact supporting evidence and document sources
Users can verify every determination, confirm validity, and make final approval with confidence.
A new decision category, “Undeterminable,” to indicate insufficient evidence
If relevant information does not exist in the RAG database, the AI will return results such as “Insufficient information” or “Unable to determine.”
This makes missing documentation visible and encourages ongoing knowledge enhancement for better future assessments.
If relevant information does not exist in the RAG database, the AI will return results such as “Insufficient information” or “Unable to determine.”
This makes missing documentation visible and encourages ongoing knowledge enhancement for better future assessments.
Case Study: JSOL
~2,000 hours of system risk assessment workload reduced per year
JSOL, a member of the NTT DATA and SMBC Group, uses AskDona Batch Assessment to support risk assessments across more than 100 systems and 400 evaluation items.
Results:
• Over 90% consistency between AI classification and human reviewers
• ~45% reduction in manual workload per system
• An expected annual reduction of ~2,000 work hours (~260 person-days)
This case demonstrates how AskDona enables standardization and efficiency in governance and compliance workflows.
👉 Read the full press release from JSOL & GFLOPS
Batch Assessment
Batch Process
Higher accuracy, faster first-level
assessment — powered by AI agents.
Batch Assessment automatically evaluates predefined assessment items and classifies each as “Compliant,” “Not compliant,” or “Not applicable,” based on verified knowledge stored in AskDona. It extends the same automation benefits of Batch Process — beyond answer drafting — into the actual assessment workflow.
AI-powered objective, high-accuracy automated decision-making
AskDona supports Excel files (.xlsx/.xls) as well as Word, PowerPoint, PDF, and many other formats.
Simply upload internal documents such as security policies or product manuals — AskDona will organize them into a searchable knowledge base automatically.
For more information about dona-rag-2.0
The AI agent applies evaluation criteria defined by administrators and references evidence retrieved using dona-rag-2.0’s high-precision search capabilities.
This ensures consistent, objective assessments — eliminating human interpretation gaps and reducing evaluation variance across reviewers.
A highly transparent decision process based on documented evidence
Each AI judgment clearly shows:
• The reasoning behind the decision
• The exact supporting evidence and document sources
Users can verify every determination, confirm validity, and make final approval with confidence.
Each AI judgment clearly shows:
• The reasoning behind the decision
• The exact supporting evidence and document sources
Users can verify every determination, confirm validity, and make final approval with confidence.
A new decision category, “Undeterminable,” to indicate insufficient evidence
If relevant information does not exist in the RAG database, the AI will return results such as “Insufficient information” or “Unable to determine.”
This makes missing documentation visible and encourages ongoing knowledge enhancement for better future assessments.
If relevant information does not exist in the RAG database, the AI will return results such as “Insufficient information” or “Unable to determine.”
This makes missing documentation visible and encourages ongoing knowledge enhancement for better future assessments.
Case Study: JSOL
~2,000 hours of system risk assessment workload reduced per year
JSOL, a member of the NTT DATA and SMBC Group, uses AskDona Batch Assessment to support risk assessments across more than 100 systems and 400 evaluation items.
Results:
• Over 90% consistency between AI classification and human reviewers
• ~45% reduction in manual workload per system
• An expected annual reduction of ~2,000 work hours (~260 person-days)
This case demonstrates how AskDona enables standardization and efficiency in governance and compliance workflows.
👉 Read the full press release from JSOL & GFLOPS
Batch Assessment
Batch Process