A commons for real-world problem solving.
OpenDiagnose is a modular, open-source diagnostic system designed to interpret the physical world through structured visual intelligence. It combines wearable or edge-mounted camera systems with interchangeable AI models and rule-based reasoning layers to detect, classify, and explain real-world problems in real time. The goal is not just to recognize objects, but to understand failures, anomalies, and degradation across mechanical, electrical, agricultural, and infrastructure systems.
At its core, OpenDiagnose is built as a layered pipeline: capture, analyze, reason, and output. Visual input is processed through computer vision models and optional domain-specific rule packs, then translated into structured diagnostic outputs that include the issue, confidence level, severity, and step-by-step repair guidance. These outputs can be displayed through a heads-up display, spoken via audio, or printed as portable repair instructions for field use.
The system is fully modular by design. Hardware components such as cameras, compute units, displays, and power systems can be swapped independently without affecting the diagnostic logic. On the software side, vision models, diagnostic engines, and knowledge databases are all replaceable modules that adhere to a shared specification. This allows the system to evolve over time without becoming dependent on a single vendor, model, or implementation.
OpenDiagnose also introduces a knowledge-driven commons layer where domain-specific “diagnostic packs” can be shared, versioned, and improved by the community. These packs contain structured failure patterns, repair workflows, and validated fixes that expand the system’s capabilities across industries. Combined with a feedback loop from field usage, the platform continuously improves its diagnostic accuracy and practical usefulness.
The result is a distributed diagnostic infrastructure for the real world: a system where perception becomes structured understanding, and understanding becomes immediate, actionable repair guidance.
This specification is released under the GNU Affero General Public License v3.0 or later (AGPL-3.0+) and may be used freely with required attribution under Section 7. A Specification Branding License is available for attribution-free deployments, with fees based on usage, scope, and deployment size.
Specification Repository:
- OpenDiagnose – A modular, AGPL-3.0+ diagnostic system that turns real-world visual input into structured, actionable repair guidance through interchangeable hardware, AI models, and knowledge packs.
Specification Pricing:
| Network Size | # of Users | One-Time Price | Duration |
| Small | 1 – 20 | $1,300,000 | Perpetual License |
| Medium | 21- 1000 | $3,200,000 | Perpetual License |
| Large | 1001 + | Custom Quote | Custom Quote |
The initial public announcement of the OpenDiagnose system design was made on Facebook on July 28, 2026, introducing the concept as a wearable, vision-based diagnostic tool capable of translating real-world visual input into structured repair guidance. At that stage, the idea was presented as a unified system focused on immediate field diagnostics and assisted troubleshooting. As the project evolved, the architecture shifted away from a monolithic design and toward a fully modular framework, separating hardware, software, and diagnostic intelligence into independently replaceable components.
This evolution was driven by the need for scalability, interoperability, and long-term maintainability. Rather than locking functionality into a single device or model stack, OpenDiagnose was restructured into a specification-first system where cameras, compute units, AI models, and knowledge packs can be swapped without breaking the overall pipeline. This modular approach allows the platform to grow across industries and use cases while preserving a consistent diagnostic schema and shared commons-based foundation.