Bring enterprise data and knowledge to reasoning and multi-agent execution systems in secure and compliant way.

Figure below illustrates our end-to-end approach to enterprise architecture that powers intelligence folowing .

Our architecture combines three building blocks:

1. Intelligence — AI reasoning and a multi-agent execution environment that coordinates tasks, uses tools and delivers answers.
2. Connected knowledge and data — A solution that brings trusted corporate knowledge and business data to AI in the right context, format and compliant to security and business rules.
3. User experience — An intuitive experience tailored to each user’s role, needs and daily work.

AnB connects AI capabilities with trusted business information and practical user experiences. The architecture is vendor agnostic: models, platforms and interfaces can evolve while preserving the customer’s business definitions, integrations and access controls.

1. Intelligence

The intelligence layer interprets a user’s request, plans the work, selects appropriate tools and combines results into a useful response. It provides AI reasoning and a multi-agent execution environment, allowing specialized agents to collaborate when a task requires different capabilities.

For example, investigating a delayed customer order may require checking order details, reviewing production information and finding relevant delivery policies.

AnB turns general AI capabilities into business-specific assistance by:

• Defining business skills, instructions and workflows that reflect how the customer operates.
• Connecting AI to approved tools for retrieving data, searching documents and interpreting business definitions.
• Coordinating tasks and passing relevant context between agents.
• Establishing boundaries for tool use, validation, exception handling and human review.
• Evaluating responses against representative business questions and monitoring operational performance.

2. Connected Knowledge and Data

This layer makes corporate knowledge and business data available to AI in the right context and format, in accordance with security requirements and business rules.

It connects structured information—such as customers, orders, products and financial measures—with unstructured information, including policies, procedures and corporate documents. Shared business definitions help AI understand what the information means and how different sources relate.

AnB creates the connection between enterprise information and AI by:

• Integrating business systems, data platforms and document repositories through reusable adapters.
• Providing consistent data views that reduce dependence on individual source-system structures.
• Defining shared business entities, relationships, terminology and mappings.
• Reusing approved business measures and rules to support consistent interpretation.
• Preparing authorized documents for retrieval, with source references and processes for keeping content current.
• Carrying user permissions through data access and document search, with controls for quality, ownership and traceability.

3. User Experience

The user experience layer makes intelligent assistance accessible within each user’s daily work. It translates the underlying capabilities into interactions suited to a person’s role, responsibilities and permissions.

The experience may take the form of a conversational assistant, a dedicated application or assistance embedded in an existing business application. Different roles can use the same underlying intelligence and information through different interfaces.

AnB designs the experience around practical business needs by:

• Custom Web application
• MCP Services for the integration with most common tools like GPT Work, Copilot and Clode.
• Applying role-based access consistently across interfaces.
• Using feedback to improve usability and prioritize further capabilities.