Both assistants feature intuitive, conversational interfaces – no specialized training is needed.
Quickly access the knowledge you need without leaving the BlueDolphin environment.
Effortlessly share insights, documents, and process overviews to keep everyone on the same page.
Explore & Learn: Provides instant insights about BlueDolphin’s features, architecture, and best practices through natural language queries.
Stay Focused: Eliminates the need to switch between BlueDolphin and separate documentation, keeping you on task.
Onboarding for All: Makes platform knowledge accessible to everyone, not just technical experts or architects.
The Knowledge AI Assistant is designed exclusively for general-purpose use. It functions solely as a natural language search engine for the BlueDolphin knowledge base without processing or accessing any of your organization’s data.
Simplify Architecture Exploration: Translates complex architecture models into clear insights using natural language
Make BPMN Simple: Translates complex BPMN diagrams into easy-to-understand visuals and shareable documentation.
Empower All Users: Enables intuitive interaction with architecture views without a technical background.
Effortless Sharing: Quickly generate and share insights from models such as application landscapes, process architectures, and solution designs.
Streamlined Collaboration: Allows quickly generating clear process overviews that can be shared with teams and stakeholders.
The AI View Assistants do process tenant data. Specifically, it reads and interprets the architecture views you create or upload within BlueDolphin when you submit a question to provide accurate answers and generate shareable insights.
How it helps you:
Natural Language Interaction: Ask questions about architecture in plain language to easily explore different perspectives.
Instant Insights: Transform architecture models into understandable, shareable content with just a few clicks.
Purpose:
Model in minutes: Turn plain language into BPMN 2.0-compliant diagrams instantly, reducing manual diagramming effort.
Make modeling accessible: Empower business users to actively design and refine workflows, accelerating collaboration with process owners, architects, and transformation teams.
Reuse what you already have: Turn existing documentation into structured BPMN simply by uploading files and prompt.
Data usage (AI Modeling Assistant):
Unlike the Knowledge AI Assistant, the Modeling Assistant processes tenant data and the process information you provide to generate the BPMN model. This includes interpreting the content of uploaded files and the prompts you submit to produce a diagram. Uploaded files may be used as contextual information for follow-up questions within the modelling flow.
How it helps you:
Prompt-to-diagram: Describe a process in plain language and receive a ready-to-edit BPMN diagram.
File-to-diagram: Upload supporting material (PNG, JPG/JPEG, PDF, TXT, DOCX; up to 10 MB) to generate BPMN from existing artifacts.
Smarter connections: When linking tasks to repository objects, get AI-driven suggestions to speed up modelling and improve consistency.
Find what you need faster: Ask questions in plain language and quickly discover the right objects, views, processes, and repository content inside BlueDolphin.
Make BlueDolphin easier to use: Help both experienced users and less frequent users navigate the platform more confidently, without needing to know exactly where information lives.
Turn architecture into guided action: Move from a question to relevant content in BlueDolphin through contextual answers and direct links, reducing time spent searching and interpreting repository data.
Unlike BlueDolphin MCP, AI Navigator is a BlueDolphin-provided AI capability that operates within the platform. To answer user questions, AI Navigator processes relevant tenant data from the BlueDolphin repository, such as objects, relationships, views, processes, and related metadata. This context is used to generate grounded responses and guide users to relevant content inside BlueDolphin.
Conversational AI interface: Ask questions in plain language and get context-aware answers grounded in your BlueDolphin repository.
Guided repository discovery: Quickly find relevant objects, views, processes, and related architecture content without needing to know where it lives.
Accessible architecture experience: Help both expert users and less frequent users work more confidently with architecture content inside the platform.
Faster path from question to action: Reduce time spent searching, interpreting models, and asking others where to find the right information.
“Where can I find the applications related to this business capability?”
“Show me the relevant views for this process.”
“What objects are connected to this application?”
Speak human to your architecture: Ask natural questions and get clear answers grounded in your BlueDolphin data and models.
Make EA accessible to everyone: Give non-architect stakeholders instant, contextual insights in plain language, multiplying the impact of the architect’s work.
Faster, better-informed decisions: Reduce waiting time for translations and reports by enabling real-time analysis and explanations through the company’s AI chatbot.
BlueDolphin MCP connects BlueDolphin to a third-party AI assistant that is provided, configured, and controlled by the Customer (e.g., Microsoft Copilot, Claude Desktop, Google Workspace Gemini). When a user asks a question in the Customer’s AI tool, the user’s prompt and the relevant BlueDolphin context needed to answer it (for example, selected projects, objects, and relationship data returned by BlueDolphin) may be shared with that third-party AI tool so it can generate a response grounded in the Customer’s architecture environment.
In this MCP scenario, BlueDolphin acts only as the provider of the MCP/API interface and the BlueDolphin data retrieval endpoint; BlueDolphin does not operate or control the third-party AI assistant or how it processes, stores, or uses prompts and outputs. The Customer’s use of the third-party AI tool (including any retention, training, logging, or other settings) is governed by the Customer’s agreement and configuration with that third-party provider.
This differs from BlueDolphin’s own AI features, where BlueDolphin provides the AI capability within the platform and the associated data usage and safeguards are governed by the BlueDolphin AI Addendum. MCP connectivity is optional and only applies if the Customer chooses to connect BlueDolphin to their own third-party tools.
Conversational AI interface: Context-aware Q&A grounded in BlueDolphin models and data.
Impact analysis on demand: Surface dependencies, risks, and continuity implications across applications, processes, and capabilities.
Role-relevant insights: Tailored outputs for executives, portfolio owners, HR, BCM, operations, and architects, delivered in accessible language.
Decision intelligence layer: Connect responses to goals and strategies to bridge strategy-to-execution.
Proactive EA enablement: Help architects shift from reactive validators to strategic partners by exposing connections earlier in planning.
“Which applications support HR onboarding?”
“What happens if this system fails?”
“What are the key dependencies and risks for this initiative?”
Delivering a seamless, intuitive, and highly efficient user experience requires continuous learning and refinement. By analyzing real-world interactions and user data, we can identify patterns, improve AI accuracy, and develop features that genuinely meet your needs. These insights allow us to make our AI smarter, more responsive, and better tailored to your workflow. Ultimately enhancing the value, you get from our platform. Our commitment is to leverage data responsibly, prioritizing transparency and user control.
We understand that privacy is a personal choice, and we are committed to giving you complete control over your data.
Opt Out Anytime: We respect your choices. If you prefer not to have your data contribute to AI model training, you can easily opt out through the in-app “Chat with support” system
Strict Access Control: Your data is never shared with third parties, and only authorized team members can access it for necessary improvements.
Privacy & Compliance First: We adhere to strict internal policies and comply with all relevant data protection laws to safeguard your information.
Your trust is at the core of everything we do. If you have any questions or concerns, please don’t hesitate to contact our support team through the in-app “Chat with support” system.
See the details in the link to the Overview of the BlueDolphin AI.
For all BlueDolphin users, the AI Assistant processes data within the same region as their tenant, meaning that EU tenants’ data will stay in the EU and US tenants’ data will stay in the US. However, exceptions may apply for certain features requiring specialized models. Any such exceptions will be clearly communicated in the release notes in advance.
Yes, BlueDolphin stores questions and answers for debugging and analysis purposes. This data is not shared with third parties and is only available to authorized BlueDolphin employees.
While the AI Assistant is developed using reliable information from BlueDolphin, it may not always provide 100% accurate results. This is due to a common issue with generative AI models known as “hallucination”, where the system might generate incorrect or misleading information. ValueBlue continuously refines the AI to minimize inaccuracies.
Users of the AI Assistant are responsible for validating the answers provided.
In an attempt to be helpful, the AI assistant can occasionally produce incorrect or misleading answers.
This is known as AI hallucination, and it’s a byproduct of some of the current limitations of generative AI models. AI hallucinations are similar to how humans sometimes see figures in the clouds. In the case of AI, these misinterpretations occur due to various factors, including model training data inaccuracies, high model complexity, or incorrect assumptions made by the model.
When working with the AI Assistant you should not rely solely on it as a singular source of truth. Always review answers given by the AI Assistant. Should you encounter any AI hallucinations, we would gladly receive your feedback through the in-app “Chat with support” system. ValueBlue incorporates feedback and invests in improvements to mitigate such inaccuracies.
In short, it is the user's responsibility to validate the answer provided by AI.
Due to the nature of AI, there is no guarantee that all issues or errors reported by users can be fixed individually. However, BlueDolphin continuously works to improve the underlying AI model through strict evaluations and updates. To submit feedback, use the in-app “Chat with support” system.
Yes, you can report any inaccuracies or bugs encountered while using the AI Assistant through our support. Although we cannot promise a fix for every issue, your feedback helps us improve the overall system. To submit feedback, use the in-app “Chat with support” system.
No, BlueDolphin does not share your data with any outside parties, and only authorized BlueDolphin employees can access it.
No, none of our LLM providers store the data you submit or the answers you receive.
The data you submit and the answers you receive are used only to serve your experience and are not shared between customers.
As part of our ongoing commitment to improving the BlueDolphin AI, we plan to train and fine-tune our models in the future. BlueDolphin maintains a strong commitment to safeguarding your data privacy and employs robust measures to protect your information
Your trust is our priority. If you have further questions or concerns, please contact our support team using the in-app “Chat with support” system.
For BlueDolphin AI products, contact your Account Manager.
For details of their capabilities, see Overview of the BlueDolphin AI.
We upgrade and change AI models using diligent controls and measurements, following the same disciplined approach we use for all product improvements. This includes validating expected behavior and performance, monitoring quality and stability, and rolling out changes in a controlled manner to minimize risk for customers.
BlueDolphin AI uses large language models accessed through Third parties (Microsoft Azure AI Foundry services). The specific model used depends on the AI capability and the performance requirements (for example reasoning quality, speed, tool calling, etc.). Models currently used may include, but are not limited to:
BlueDolphin may update or change the specific model versions over time to ensure optimal quality, performance, and security.
The underlying models are third-party foundation models provided through Microsoft Azure’s enterprise AI services.
These are not public consumer services. They are accessed through Microsoft’s enterprise Azure environment, which provides:
The foundation models themselves are trained by the model provider on large general-purpose datasets. BlueDolphin does not control or contribute to the original foundation-model training dataset
Importantly:
The AI capabilities run within Microsoft Azure cloud infrastructure.
Azure provides the underlying:
The generative AI models are accessed through Azure AI Foundry services in enterprise Azure environments provided by Microsoft.
Regarding the region: the services run in the same region as the customer’s tenant, which is either US or EU.
No, for native AI capabilities inside the BlueDolphin platform. BlueDolphin currently operates the AI models through its managed Azure environment to ensure consistent quality, performance, and security. However, we recognize that some organizations may require the use of customer-controlled models for governance or compliance reasons. Supporting customer-provided models for certain native AI capabilities may therefore be considered as part of the future product roadmap.
Yes, for MCP integrations. BlueDolphin supports scenarios where customers can connect their own AI assistant or LLM environment through Model Context Protocol (MCP) integrations (for example via tools such as Claude Desktop, Microsoft Copilot or other enterprise AI assistants)
In this scenario:
This allows organizations to use their own approved AI models or AI platforms while leveraging BlueDolphin’s enterprise architecture repository as contextual data.
To support operational monitoring and troubleshooting we log relevant information about AI interactions. Logged data may include prompts and AI outputs, along with technical metadata (e.g., timestamps, tenant/organization identifiers, and error information). We retain this data for 12 months, after which it is deleted in accordance with our retention policy.
We upgrade and change AI models using diligent controls and measurements, following the same disciplined approach we use for all product improvements. This includes validating expected behavior and performance, monitoring quality and stability, and rolling out changes in a controlled manner to minimize risk for customers.
To stay informed about the latest developments and changes to BlueDolphin AI, please join our community.
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