From manual tasks to autonomous workflows
Intelligent agents that automate tasks, orchestrate workflows, and adapt as your business grows.

Autonomous AI, tailored to your needs
Single agents, multi-purpose frameworks, or fully orchestrated workflows — choose the level of autonomy that fits your business.
Providing autonomous AI Agents focused on specific, isolated tasks within a narrow domain.
Building robust frameworks for autonomous AI Agents capable of independently executing processes and complex tasks.
AI Agentic Workflows made up of one or more intelligent agents that can perceive their environment, make decisions, and take actions to achieve specific goals – often autonomously or with minimal human intervention.
See how AI Agent works
AI Agent autonomously processes text, voice, and video inputs, taps into data, models, and knowledge bases, and drives business actions with human oversight where needed for maximum accuracy and efficiency.
Goal Definition
AI Agent is given a goal or task (manually or autonomously).
Input Gathering
AI Agent gathers data from the environment, such as: text input from the user, API responses, documents, databases, logs, sensors etc.
Planning
AI agent creates a plan based on: the goal, the current context, available tools or actions.
Action
AI agent takes action, such as: calling APIs, send sms/emails, answer generation, task summary, report and document generation. etc.
Evaluation
AI Agent checks the result of its action:
- was the task completed?,
- was the output valid or useful?,
- are there errors or follow-ups?
If not done, it goes back to planning and tries again.
Termination
AI Agent either:
- Ends the task successfully, or
- Adjusts and loops again
- Escalates to a human if it’s needed
How AI Agent Systems work
AI Agent Systems / G.Tx Workflows made up of one or more intelligent agents that can perceive their environment, make decisions, and take actions to achieve specific goals – often autonomously or with minimal human intervention.
Autonomy
Agents operate independently without continuous human guidance.
Perception
They gather information from their environment (e.g., via APIs, sensors, databases).
Decision-making
They use logic, rules, or learning models to make decisions.
Action
They perform tasks like sending messages, updating records, triggering workflows, etc.
Goal-oriented
Agents are designed to pursue specific objectives.
Real results from autonomous AI
Time saved, errors reduced, decisions improved - and the flexibility to scale on demand.

Time and cost savings
Reducing the burden of manual tasks on employees and increasing operational efficiency.

Error reduction
Automation minimizes the risk of errors caused by human oversight.

Scalability
Adjusting the number of AI agents to match current business needs.

Improved decision-making
Advanced data analysis algorithms support more accurate and data-driven decisions.
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