Singulr AI Glossary

Agentic workflows are multi-step business processes that are planned and executed by AI agents with varying degrees of autonomy. Instead of a human orchestrating each step, an AI agent receives a goal, breaks it down into tasks, decides which tools to use, and works through the sequence — checking results and adjusting its approach along the way. These workflows matter because they represent the next level of AI-driven automation. Traditional automation follows rigid, predefined scripts — if step two fails, the whole process stops. Agentic workflows are adaptive. The agent can try alternative approaches, gather additional information, or ask for human input when it encounters something unexpected. This makes them suitable for tasks that are too complex or variable for traditional rule-based automation. A typical agentic workflow might involve an agent receiving a request to prepare a competitive analysis. The agent would search internal documents, pull relevant market data, synthesize findings into a draft, check the draft against a style guide, and deliver the final report — making dozens of tool calls and decisions along the way. More complex workflows involve multiple agents collaborating, each handling a different part of the process. For enterprises, agentic workflows introduce governance challenges that traditional automation didn't. Because the agent is making real-time decisions about what to do next, organizations need controls that work dynamically — not just at the start and end of a process, but at every step. This includes monitoring what data the agent accesses, which tools it invokes, and whether its actions align with company policies, especially in regulated environments where every decision may need to be explainable and auditable.