Service

AI Agent Solutions

A new generation of intelligent assistants: AI Agent–based architecture and MCP

BlueAI Assistants are more than single LLM-based solutions. In our latest architecture, we also leverage AI Agents and MCP (Model Context Protocol) technology. This enables the creation of systems capable of executing real business processes, communicating with external systems, and taking actions in line with defined security policies.

As a result, BlueAI becomes a flexible and scalable platform that can grow with the organization—whether you need a single assistant or an entire network of cooperating agents.

AI Agents as the foundation of process automation

Within BlueAI solutions, we use an agent-based architecture built around so-called isolated AI Agents, each responsible for specific business tasks and designed to be extended or further developed by our clients.

Our assistants:

can operate independently or leverage a set of supporting agents,
are compatible with MCP servers, enabling operations on data, systems, and tools,
can be easily connected to client-developed agents, such as custom integration, automation, or decision-making modules,
remain fully compliant with organizational security and governance rules.

In this architecture, MCP acts as a “secure bridge” between the agent and internal systems. It allows agents to perform operations (e.g. queries, data modifications, file retrieval, system updates) in a strictly controlled and monitored environment.

Scalability through AI Agent and MCP architecture

Unlike traditional chatbots, our solutions are designed as modular agent systems that can be:

freely extended by adding new agents responsible for additional processes,
replaced or updated without impacting the entire system,
connected to client-owned agents (e.g. automating finance, sales, or logistics processes),
reused across projects thanks to MCP-based architecture and StarBoost for AI services.

This approach allows clients to start with a single assistant and gradually build a full AI agent platform that automates an increasing share of business processes.

Examples of AI Agents used in our implementations

In practice, we have already implemented a set of agents who:

Analyzing documents received via email

Agents independently:

classify incoming messages,
extract relevant data,
complete document sets,
route them to appropriate systems (CRM, ERP, ticketing).

This reduces manual analysis time by up to 80–90%.

Accessing and modifying data in sales systems

Example agents:

analyze customer data,
synchronize information between CRM and operational systems,
support sales teams in offer preparation, pricing analysis, and activity prioritization.

All actions are performed via MCP, ensuring full control and traceability.

Collecting hotline requests and automating follow-up processes

Agents analyze call content and:

create service tickets,
classify cases,
extract key information,
route requests to the appropriate department.

This delivers not only automation, but also standardized, consistent quality in incident and inquiry handling.

Evolving agent capabilities in a secure environment

Each agent operates within a strictly defined, secure environment with a limited set of tools and permissions. Agent capabilities are expanded gradually, based on:

organizational maturity,
level of trust in automation,
risk assessment,
the client’s readiness to delegate control.

This phased approach enables the development of increasingly autonomous yet secure systems—fully aligned with EU AI Act requirements and enterprise security principles.

AI Agents as the automation platform of the future

Thanks to the AI Agent + MCP architecture, BlueAI is not a traditional chatbot, but:

a dynamic platform of intelligent agents,

ready to integrate with client systems and internally developed agents,

enabling step-by-step automation of additional processes,

operating in full compliance with security policies,

scalable and future-ready for evolving business needs.

FAQ

What are AI Agents and how do they differ from traditional assistants or chatbots?

AI Agents represent a new generation of intelligent systems that go beyond answering questions. They are capable of independently executing concrete business processes. AI Agents can make decisions, perform actions in external systems, collaborate with other agents, and operate in accordance with predefined rules and security policies.

At BlueAI, we use an agent-based architecture built on AI Agents and MCP (Model Context Protocol) technology. This allows us to create systems that operate effectively in real enterprise environments, not just generate text-based responses.

Can AI Agents integrate with client systems?

Yes. AI Agents deliver the greatest value when they are deeply integrated with systems used across the organization.

With BlueAI, agents can work with CRM and ERP systems, ticketing platforms, communication tools, and custom client solutions via MCP as well as dedicated integrations and connectors.

What can AI Agents be used for within an organization?

AI Agents are well suited to processes that require working with data, systems, and executing sequential actions. They can automate document handling, system integrations, data analysis, request processing, and sales support.

In BlueAI, agents are designed to perform specific business tasks, either independently or as part of a larger ecosystem of cooperating agents.

How scalable are agent-based solutions?

Agent-based solutions are designed as modular systems that can be gradually expanded as the organization grows.

With BlueAI, it is possible to:

add new agents responsible for additional processes,
update or replace agents without impacting the entire system,
reuse agent logic across other projects thanks to MCP-based architecture and StarBoost for AI services.

Clients can start with a single assistant and progressively build a full AI Agent platform that automates an increasing share of business processes.

How does the agent-based architecture work in BlueAI?

The agent-based architecture relies on isolated AI Agents, each responsible for a defined scope of tasks and equipped with clearly specified permissions. Agents can operate independently or leverage other supporting agents.

In BlueAI, agents are compatible with MCP servers, enabling them to securely perform operations on organizational data, systems, and tools. They can also integrate with client-developed agents, such as decision-making or automation modules.

What examples of AI Agents are used in practice?

AI Agents can support highly specific business scenarios, including:

analyzing documents received via email (classification, data extraction, system routing),
accessing and modifying data in sales systems and supporting sales teams,
automating hotline request handling and downstream processing.

With BlueAI, such implementations can reduce manual work by up to 80–90%, while improving process quality and consistency..

What is MCP and what role does it play in agent-based solutions?

MCP (Model Context Protocol) acts as a secure bridge between AI Agents and organizational systems. It enables agents to perform actions such as system queries, data modifications, and file handling—always within a controlled and monitored environment.

In BlueAI, MCP ensures full compliance with security, governance, and auditability requirements, which are critical in enterprise environments.

Are AI Agents secure and compliant with regulations?

Security and control are fundamental to agent-based architectures. Each agent operates within a strictly defined environment with a limited set of tools and permissions.

In BlueAI, agent capabilities are expanded gradually, based on organizational maturity, risk assessment, and readiness to delegate control. Solutions are designed in line with enterprise security principles and EU AI Act requirements.