Automation Anywhere vs DX

A conversational generative-AI assistant embedded inside business applications such as SAP, Workday and Salesforce that turns natural-language requests into built and deployed automations, using the Process Reasoning Engine for business context.

Intelligent document processing that uses natural language processing, computer vision and generative AI to classify, extract and validate data from structured, semi-structured and unstructured documents including handwriting, barcodes and free-form text.

Records how work is actually done on employees' screens with computer vision, uses AI to uncover every process variation and map it, redacts personal data through a Privacy Enhanced Gateway, and ranks which processes to automate next. Part of the Agentic Process Automation Platform.

A generative automation builder that takes intent from plain language, SOPs, BPMN diagrams, screenshots or voice, produces a structured plan for review, then generates agents, API tasks, processes, forms and bots as governed production automations.

A set of generative-AI tools for the people who build automations on Automation Anywhere's platform: Autopilot turns process documents into ready-to-deploy automations, Co-Pilot for Automators builds steps from natural-language prompts, and Generative Recorder adds a GenAI fallback so workflows keep running when a screen changes. Part of the Agentic Process Automation Platform.

A test environment that runs an end-to-end workflow before it goes live: simulation mode generates test data and models each step's output without touching live systems, AI proposes extra scenarios and edge cases across APIs, bots, agents and human steps, and the results point at gaps and broken branches to fix. Part of the Agentic Process Automation Platform.

DX AI is a conversational interface for exploring an organization's engineering data held in DX, described by the vendor as 'the copilot for engineering leaders.' It answers natural-language questions with generated charts, summarizes qualitative snapshot data into themes and sentiment, and diagnoses the drivers behind metric changes. Its data can also be streamed into external LLM clients via the DX MCP server.

AI Code Insights measures what AI coding agents produce inside an engineering organization, tracking AI-generated code by commit, PR, team, agent and repo from IDE to production. It attributes authorship by monitoring supported coding agents' edits and links them to commits, pull requests and deployments, reporting adoption, delivery velocity, code-quality signals and session-level agent performance. It includes the Agent Experience report, which scores requirements clarity, steering and task scope from the agent's perspective.

Command-line interface to a DX instance, built so coding agents can drive it: it ships an agent skill telling an agent when and how to call the CLI, and covers the same catalog, scorecard and self-service operations a human uses the dashboard for.

Fabric is DX's context layer for AI agents, marketed as 'the context engine for AI-native engineering.' It turns an organization's software catalog into structured, live context that agents can query, and adds scorecards and self-service automation so agents can create services, provision infrastructure and resolve failing standards checks. Context is exposed to any MCP-compatible agent via the DX MCP server.