Focused product visions that could one day work together. Each division addresses a distinct engineering challenge.
Concept is used conservatively: no implementation evidence has been provided for the listed capabilities.
Concept
01 / Intelligent robotics & autonomous systems
AutoDigda Robotics
A vision for robotic platforms that perceive their surroundings, build meaningful maps, and navigate with purpose.
The engineering challenge
Robots must do more than follow a path. They need to estimate where they are, interpret changing surroundings, and operate within clear physical constraints.
Planned capabilities
SLAM and autonomous navigation
Semantic perception and mapping
Embodied AI and computer vision
Robotic control and mobile inspection
Who it is designed for
Robotics researchers, industrial engineers, educators, and teams exploring warehouse or inspection automation.
An envisioned AI assistant for exploring circuit architectures, selecting components, and preparing simulation workflows.
The engineering challenge
Turning electrical requirements into a reliable design requires component research, simulation, and careful validation. Amadeus aims to make those exploration loops easier to navigate.
Planned capabilities
Natural-language circuit requirements and schematic assistance
Component recommendations with engineering constraints
SPICE simulation preparation and circuit analysis
Design error detection, optimization, and potential PCB assistance
Who it is designed for
Electronics engineers, hardware builders, researchers, and students designing or studying circuits.
A planned engineering assistant for explaining PLC logic, exploring control programs, and preparing simulation-led validation.
The engineering challenge
Control logic must account for sequences, interlocks, I/O behavior, and failure conditions. AI assistance is useful only when it supports explicit engineering review.
Planned capabilities
Natural-language control requirements and I/O mapping assistance
Ladder Diagram assistance and Structured Text generation
Program explanation, debugging, and logic validation
Simulation and virtual commissioning exploration
Who it is designed for
Automation engineers, system integrators, maintenance teams, and industrial engineering educators.
04 / AI agent orchestration & engineering automation
Jarvis
An envisioned orchestration layer for coordinating specialized AI agents, development tools, and human decisions across engineering projects.
The engineering challenge
Engineering projects span code, research, tools, and decisions. Jarvis aims to make responsibilities, progress, and approval boundaries visible in one coordinated workflow.
Planned capabilities
Task planning, delegation, and multi-agent coordination
Coding agent and engineering tool integration
Multi-project monitoring and remote development workflows
Real-time task visibility and human-in-the-loop approvals
Who it is designed for
Engineering teams, independent builders, researchers, and developers managing complex projects.
One long-term vision. Four focused disciplines. Select a domain to explore how it could fit into an AI-native engineering workflow.
AAUTODIGDA
Concept
Jarvis
Jarvis is envisioned as internal development infrastructure for AutoDigda, and potentially a future commercial product. It could coordinate tasks across Amadeus, PLC AI, and Robotics.