Tnkr is a cloud‑native platform that unifies hardware BOMs, CAD files, firmware, datasets, and AI models for robotics projects, offering Git‑style version control and CI/CD integrations with tools such as Onshape, SolidWorks, and GitHub. Its on‑device AI assistant, Leonardo, creates interactive assembly guides from build videos and CAD data, provides real‑time troubleshooting, and the built‑in Fleet marketplace links robot owners with paid data‑collection and model‑testing tasks.
Funding
Funding not disclosed
Founders
Product
Problem
Open‑source robotics projects often rely on disparate tools for hardware schematics, firmware, datasets, and AI models, making it difficult to reproduce builds, track contributions, and keep documentation up to date. The lack of automated, context‑aware documentation further slows onboarding and limits the scalability of community‑driven robot development.
Solution
Tnkr consolidates the four pillars of physical intelligence—hardware, software, data, and models—into a single cloud‑native workspace. The platform lets creators publish BOMs, CAD files, source code, and operational datasets alongside version‑controlled AI models. Leonardo, an on‑device AI assistant, ingests first‑person build videos, CAD geometry, and code to generate step‑by‑step assembly guides, suggest design improvements, and troubleshoot issues in real time. Integrated connectors to Onshape, SolidWorks, GitHub, Slack, and other dev‑ops tools enable seamless data flow and continuous‑integration pipelines. Collected robot telemetry can be fed directly into training pipelines, closing the loop between deployment and model refinement. A built‑in Fleet program matches hardware owners with paid data‑collection and model‑testing tasks, turning community robots into revenue‑generating assets.
Target Audience
The primary users are robotics engineers, hobbyist makers, and research labs that develop open‑source hardware and need a collaborative environment for code, data, and AI model management; enterprise teams building proprietary robots also use the private‑repo tiers.
Features
- Unified project repository that stores BOMs, CAD assemblies, firmware, datasets, and Vision‑Language‑Action models with Git‑style version control
- Leonardo AI transforms POV build videos and CAD data into interactive, step‑by‑step assembly documentation and provides real‑time troubleshooting suggestions
- Automatic data ingestion pipeline that captures sensor streams and logs, then routes them to cloud‑based training jobs or analytics dashboards
- 3‑D interactive visualizer allowing users to explore, rotate, and annotate robot components directly in the browser
- Native integrations with Onshape, SolidWorks, Fusion 360, GitHub, Slack, Notion, and other enterprise tools for end‑to‑end CI/CD workflows
- Remix Mode with AI‑assisted forking and modification of existing project files, supporting collaborative iteration
- Fleet Program marketplace that matches robot owners with paid data‑collection or model‑validation tasks, with earnings tracked per hour
- Role‑based access controls, audit logs, and FIPS‑compliant encryption for both public and private repositories