Automation Anywhere

Automation Anywhere is an enterprise Agentic Process Automation platform, the mature evolution of its market leading robotic process automation business into a system that coordinates AI agents, bots, APIs, and human decisions across entire business processes. Founded in 2003 in San Jose as Tethys Solutions by Mihir Shukla, Neeti Mehta Shukla, Ankur Kothari, and Rushabh Parmani, and rebranded in 2010, it raised about eight hundred forty million dollars across its Series A and Series B, including a three hundred million dollar investment from the SoftBank Vision Fund and a two hundred ninety million dollar Series B led by Salesforce Ventures at a six point eight billion dollar valuation. It has been named a Gartner Magic Quadrant Leader for robotic process automation for eight straight years and serves thousands of organizations across ninety countries.

The platform is built around the Process Reasoning Engine, which Automation Anywhere positions as the first reasoning engine purpose built for enterprise process automation. Rather than exposing all enterprise data to every step, its Context Intelligence Graph draws on more than four hundred million automation executions to retrieve only the context each task needs, connecting to systems of record, documents, policies, and execution history. The Mozart Orchestrator unifies agents, automations, documents, and APIs into governed dynamic workflows, and the low code AI Agent Studio lets teams build goal driven agents, assign each a role and tool access, and route work with human handoffs. It is deliberately model agnostic, connecting to foundation models from Amazon Bedrock, Google Vertex AI, Azure OpenAI, and OpenAI rather than hosting its own, and a January 2026 collaboration with OpenAI pairs those reasoning models with the engine for a full reasoning to action loop.

Governance runs the length of the lifecycle: AI Guardrails, data masking, audit, AI Evaluations that grade agents at design and run time, and a process simulation and testing environment for rehearsing failures before production, with agentic execution deployable inside a customer virtual private cloud for data control. The company reports more than thirty percent higher accuracy from agents using the reasoning engine with the context graph, and cites straight through processing above ninety percent and IT service desk auto resolution near eighty percent. For a large or regulated enterprise that already runs automation at scale and wants to extend it into governed agentic operations, Automation Anywhere is a category leading option; a small team wanting a quick single purpose agent will find the platform heavier than it needs.