Casimir Bajarla@TheLegendaryGrim

The Problem Traditional RPA relies on rigid code, web scrapers, and APIs. When UIs change, bots crash, halting productivity and driving up expensive developer maintenance costs. The Solution Automato is a Vision-Native Agentic RPA platform that bridges natural language and physical OS execution. Instead of relying on astronomically expensive full-parameter fine-tuning, Automato uses a Pinecone vector database and Retrieval-Augmented Generation (RAG) to dynamically ground Qwen 3.6’s inference. It visually scans applications and seamlessly executes mouse clicks and keystrokes via pygetui. If a human can see it and click it, Automato can automate it. Target Audience Enterprise automation is taken from engineers and given directly to the non-technical workforce—office managers, accountants, and operators—who perform the daily tasks. Unique Features & Benefits Zero-Code Playbooks: Build cross-platform workflows simply by uploading a screenshot and typing a plain-English instruction. Absolute UI Immunity: Qwen 3.6 uses semantic vision instead of brittle DOM scraping. If a portal changes its design, the agent dynamically adapts. Human-in-the-Loop (HITL): If the AI encounters an ambiguous screen and confidence drops, it securely pauses and alerts a human for guidance. API-Independent: Extracts data from modern cloud apps and types it directly into closed, 20-year-old legacy systems. Decoupled Architecture: Parallelizes Qwen 3.6's cloud "Brain" (bypassing fine-tuning costs via Pinecone) while serializing local "Muscle" (pygetui) to guarantee OS stability. Core Functions Users can automate workflows using customizable templates triggered by voice or chat, and screenshots. As the system interacts with apps, all state changes and HITL interventions are logged into Pinecone. This feedback loop ensures Qwen 3.6 dynamically learns to resolve ambiguities and create robust workflows on the fly.

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