How It Works

Tila uses a multi-agent architecture to expand the capabilities of artificial intelligence beyond a single request and give users tools for solving complex tasks in an interactive environment.

What is the agent-based approach?

In the context of Tila, an agent is an autonomous AI component capable of:

• interpreting user tasks,
• making decisions based on context,
• interacting with other agents,
• accessing external knowledge sources (such as the internet or databases),
• performing specific actions: generating text, creating images, processing documents, writing code, and more.

Multi-agent system

Instead of a linear query to a single model, Tila builds a chain of reasoning, where agents:

• break a task into subtasks,
• determine the optimal tools and models,
• coordinate execution based on the current context,
• form a final result that can be scaled or further refined.

Each tile on the canvas can represent a call to one or several agents, and the connections between them transfer knowledge, context, or data.

Advantages of the approach

• Contextual awareness: agents see the entire chain, not just a single request.
• Flexibility: you can combine different models and tools.
• Iterativity: it’s easy to refine results, clarify requests, and develop branches of thought.
• Collaboration: the structure of agent interaction mimics the distributed work of a team of specialists.