Sidecar Vision
If a human can see it and operate it, Sidecar can become the AI operator layer.
AI is trapped inside cooperative software.
Most AI automation works only when software exposes an API, plugin, browser interface, agent framework, or vendor-approved automation layer.
But much of the world's valuable computing work happens inside systems that are old, locked down, air-gapped, custom, regulated, terminal-based, or unsupported.
These systems are still operated by humans because the human interface is often the only reliable interface left.
Modern AI Automation
- APIs and webhooks
- Browser extensions and plugins
- Agent frameworks
- App integrations
Unreached Systems
- Terminals and mainframes
- Air-gapped machines
- Locked enterprise apps
- Custom operating systems
Sidecar does not wait for every system to become AI-ready. It uses the interface that already exists.
Sidecar turns the human interface into an AI interface.
Sidecar observes the target system, interprets what a human operator would see, plans safe next actions, and sends input through control channels the target system already accepts.
Observe
Sidecar captures or receives the target system's visible state: screen, terminal text, interface layout, cursor location, system responses, or other human-readable output.
Decide
An AI operator interprets the state, follows task instructions, applies policy limits, and selects the next permitted action.
Execute
Sidecar sends input to the target system using the most appropriate channel: keyboard, mouse, accessibility pathway, terminal commands, hardware input emulation, or other human-equivalent control.
A simple example: AI operates a legacy terminal.
Imagine a locked-down enterprise terminal with no API, no modern integration layer, and no AI support. A human operator normally logs in, searches a record, updates a field, and submits the change. Sidecar allows an AI operator to assist with that same workflow.
Task
Update a customer record in a legacy terminal system.
System
No API. No plugin. No software modification. Terminal-style human interface only.
Flow
Operation Flow
Credential Flow
AI can operate the system without seeing the secrets.
Full AI computer control has a fatal enterprise problem: the AI may see passwords, recovery phrases, banking codes, admin tokens, identity credentials, one-time codes, or private keys.
Sidecar separates operation from authority. The AI can navigate the workflow. The secure bridge handles the secret. The human, device, organisation, or policy engine controls approval.
AI Operator
Sees tasks, screens, states, and permitted actions.
Secure Bridge
Handles passwords, tokens, keys, one-time codes, and other sensitive secrets.
Policy Authority
Defines when a secret can be used, by whom, for which system, and under what conditions.
The AI does not need to know the secret to complete the task.
Architecture
Security Features
- Blind credential pass-through
- Human approval option
- Policy-controlled release
- Audit trail
- Least-privilege access
- No plain-text credential exposure to AI
- Optional air-gapped or local-only deployment model
External AI operation through human-observable output and human-equivalent input.
Sidecar is an external control layer. It can operate beside the target system rather than inside it. This makes it suitable for environments where changing the target system is expensive, impossible, risky, or forbidden.
AI path and credential path remain separate
Vision Interpreter
Reads the state of the target system from what a human would see.
AI Planner / Operator
Decides the next safe action based on the task and observed state.
Policy and Safety Layer
Limits what the AI may do, when it must stop, and when human approval is required.
Action Engine
Sends human-equivalent input to the target system.
Secure Credential Bridge
Passes secrets directly to the target device or application without exposing them to the AI.
One architecture. Many unreachable systems.
Legacy Enterprise Systems
Operate workflows where no modern API exists and replacement would be expensive or risky.
Mainframes and Terminals
Bring AI assistance to green-screen, command-line, and old iron systems still running critical business processes.
Air-Gapped Machines
Assist secure systems without turning them into cloud-connected AI endpoints.
Industrial and Embedded Systems
Operate minimal, custom, or device-specific operating systems through the existing human interface.
Locked-Down Enterprise Apps
Automate repetitive workflows without modifying the core system or breaching change-control rules.
Government and Regulated Systems
Support human operators in environments where auditability, policy control, and credential isolation matter.
Consumer Productivity
Give users AI help across apps, websites, files, settings, and workflows — not only where Apple, Microsoft, Google, or an app vendor allows it.
Accessibility-First Wedge
Use accessibility-style operation as the fastest way to learn, deploy, and prove value — while preserving the broader architecture.
Accessibility is the first adoption and learning wedge. The invention is not limited to accessibility. Sidecar is a general AI operator layer for human-operated computing systems.
Why existing automation does not reach this territory.
| Existing Approach | Where It Works | Limitation | Sidecar Difference |
|---|---|---|---|
| API Automation | Modern software with exposed APIs | Useless where no API exists | Operates through the human interface |
| Browser Agents | Web workflows | Weak outside browser contexts | Works across devices, apps, terminals, and operating systems |
| Robotic Process Automation | Structured enterprise workflows | Fragile, app-specific, and often brittle when screens change | Vision/state-driven AI operator model |
| Accessibility Tools | Human-assistive computer access | Designed for people, not autonomous AI operation | Uses accessibility as one control path inside a broader AI control architecture |
| Remote Desktop | Human remote control | Still requires a human operator | AI operates with policy limits and credential separation |
| OS-Native AI Assistants | Supported operating systems and approved integrations | Vendor-controlled and platform-limited | User-controlled, cross-system, and external |
| App-Specific Copilots | One vendor's app | Cannot operate the user's full computing environment | Operates across systems through the interface layer |
API Automation
Browser Agents
Robotic Process Automation
Accessibility Tools
Remote Desktop
OS-Native AI Assistants
App-Specific Copilots
Accessibility is the ramp, not the ceiling.
Accessibility pathways are valuable because they expose real interface structure, permission models, input methods, and user workflows.
That makes accessibility an ideal first wedge for learning and adoption.
But Sidecar's core idea is broader: any system a human can operate can potentially become AI-operable through visible output, human-equivalent input, and policy-controlled secret handling.
Accessibility teaches Sidecar how humans operate computers. The market is every system still operated by humans.
From apps to operators.
The first wave of AI software answered questions. The next wave will operate computers.
Most companies are trying to make AI work inside their own applications, browsers, or operating systems.
Sidecar takes a different path: it turns the existing human interface into the operating layer for AI.
Android opened mobile computing beyond one device maker and one closed stack. Sidecar aims at the next opening: AI operation beyond one app, one browser, one operating system, or one vendor-controlled automation layer.
This is not another AI app. It is a control layer for the software and machines that AI cannot otherwise reach.
Status
Prototype Direction
Sidecar Runtime and Sidecar Dot demonstrate the direction of an external AI control layer.
Current Wedge
Accessibility-style operation is the fastest practical learning and adoption path.
Expansion Field
The same architecture extends toward legacy enterprise systems, mainframes, terminals, air-gapped environments, command-line systems, custom operating systems, and consumer productivity.
IP Focus
The intellectual property focus is external AI operation of target systems through human-observable output, human-equivalent input, and secure blind credential pass-through.
Near-Term Proof
The next proof point is a short working demonstration of Sidecar operating a system with no API while keeping credentials hidden from the AI.
The Ask
We are looking for one strategic validator who understands platform shifts, human-computer interfaces, AI operation, and the commercial path from wedge use case to operating layer.
The goal is to pressure-test:
- The architecture
- The first enterprise wedge
- The security model
- The demonstration path
- The most natural licensing, funding, or platform partnership route
The right validator does not need to buy the product. They need to understand whether this is a real platform opening.Request private Sidecar Vision briefing
Sidecar Vision
AI operation for systems with no API.
If a human can see it and operate it, Sidecar can become the AI operator layer — with secure credential pass-through to keep secrets out of the AI's view.
Contact
Ric Richardson
Sidecar Vision