Ukrainian startup Dynamiq has developed a platform for orchestrating agent-based AI systems and workflows built on large language models and RAG

From simple solutions to complex systems

Using Dynamiq, developers can not only solve trivial problems, but also create complex systems. All thanks to the flexible modular design, which makes Dynamiq a universal tool for different types of projects.

This means that you can, for example, translate or summarize text using a single module or manage the interaction of multi-agent systems for complex tasks, with different levels of monitoring and clear tracing.

Low-code approach with high efficiency

The Dynamiq platform’s big advantage is its intuitive, low-code workflow builder. It makes it easy to build, test, and deploy AI solutions. It also offers:

• Ready-made modules for working with LLM, RAG and knowledge base integration.
• Ability to add Python code to create custom solutions.
• Integration with external tools and APIs, such as vector databases or cloud provider services.

Technological features of Dynamiq

Agent AI

Dynamiq uses LLM agents that can interact with each other and with external tools. The platform offers agents such as:

• ReAct agents (for automating multistep tasks).
• Reflection agents (plan and form structured actions).
• Adaptive Orchestrators (manage the collaboration of multiple agents to perform complex tasks).

Retrieval-Augmented Generation (RAG)

As you know, RAG combines generative models with topical information retrieval. Dynamiq supports both classic and Agentic RAG for:

• Document indexing: Processing PDF files, converting them to vector data and storing them in databases such as Pinecone, Qdrant and others.
• Finding relevant information: Quick access to the necessary data based on the user’s query.
• User response generation: Use for chatbots, search engines, and information tools.

Open source and community support

Dynamiq is built on open source and available on GitHub, which adds transparency, support, and flexibility to the platform. Developers can review the structure and logic of the platform, and the community can improve the framework and add new features. In addition, the library supports Python 3.10+ and includes examples for working with LLM, multi-agent systems, and RAG.

Additional technical advantages

Dynamiq supports on-premises, hybrid, and cloud environments, and integration with AWS, Azure, or GCP allows you to scale systems without losing control of your data. The platform simplifies LLM configuration for specialized tasks with data security guarantees.

In addition, thanks to Memory modules, the platform allows you to create chatbots with the ability to store and take into account interaction history (both short-term and long-term).

A team committed to innovation

Dynamiq is a team of AI enthusiasts who are constantly pushing the boundaries of what’s possible. From optimizing workflows to building modern agents and intuitive tools, we’re always striving for more.