SyntetiQ DaaS — Dataset and Model Lifecycle Platform for AI Robotics (euROBIN MS3, INRIA-reviewed)
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Zenodo
2026
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| _version_ | 1866902173823008768 |
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| author | Makar syntetiq |
| author_facet | Makar syntetiq |
| contents | <p>SyntetiQ DaaS is a web platform for end-to-end machine-learning dataset management and model training, designed to support AI-driven robotics workflows. It is built on top of OroPlatform 7 / Symfony 7.4 and integrates with NVIDIA Omniverse Isaac Sim for synthetic-data generation, with multiple pluggable training engines (Ultralytics YOLO, PyTorch SSD, Jetson).</p> <p>Functional bundles: - ModelBundle — ML model management, training-engine configuration, builds, QA reports. - DataSetBundle — image dataset import (ZIP / chunked upload), Svelte 5 bounding-box annotation editor, label management, export. - OmniverseBundle — synthetic-data generation via NVIDIA Omniverse; calls the SyntetiQ IsaacSimApp REST service. - DemoDataBundle, SetupBundle — demo fixtures and onboarding.</p> <p>Tech stack: PHP 8.5 / Symfony 7.4 / OroPlatform 7.0; PostgreSQL 16 + Redis; Svelte 5; Node.js 24 / pnpm 10; Python / conda for training scripts; Docker for development.</p> <p>This archive captures the v1.0.0 release, delivered for Milestone 3 of the euROBIN 3rd Open Call Technology Exchange Programme (Sub-Grant Agreement euROBIN_3OC_8, project "Enhancing AI-Driven Robotics Through High-Fidelity Synthetic Data for Simulation-Based Learning"). Hosting Technical Partner: INRIA (Serena Ivaldi). The MS3 deliverable was reviewed and approved by INRIA on 30 April 2026.</p> <p>The accompanying SyntetiQ stack components are archived on Zenodo under DOIs 10.5281/zenodo.19818731 (IsaacSimApp — synthetic-data generator) and 10.5281/zenodo.19819084 (RoboLab — TIAGo data collection). The continuously updated source is on GitHub at https://github.com/syntetiq/syntetiqdaas.</p> <p>Released under the Apache License 2.0.</p> <p>Funded by the European Union — euROBIN, the European Robotics and AI Network (Horizon Europe Grant Agreement 101070596).</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19818727 |
| institution | Zenodo |
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| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | SyntetiQ DaaS — Dataset and Model Lifecycle Platform for AI Robotics (euROBIN MS3, INRIA-reviewed) Makar syntetiq euROBIN euROBIN_3OC_8 SyntetiQ synthetic data MS3 INRIA-reviewed dataset management model training object detection YOLO PyTorch OroPlatform Symfony Omniverse DaaS <p>SyntetiQ DaaS is a web platform for end-to-end machine-learning dataset management and model training, designed to support AI-driven robotics workflows. It is built on top of OroPlatform 7 / Symfony 7.4 and integrates with NVIDIA Omniverse Isaac Sim for synthetic-data generation, with multiple pluggable training engines (Ultralytics YOLO, PyTorch SSD, Jetson).</p> <p>Functional bundles: - ModelBundle — ML model management, training-engine configuration, builds, QA reports. - DataSetBundle — image dataset import (ZIP / chunked upload), Svelte 5 bounding-box annotation editor, label management, export. - OmniverseBundle — synthetic-data generation via NVIDIA Omniverse; calls the SyntetiQ IsaacSimApp REST service. - DemoDataBundle, SetupBundle — demo fixtures and onboarding.</p> <p>Tech stack: PHP 8.5 / Symfony 7.4 / OroPlatform 7.0; PostgreSQL 16 + Redis; Svelte 5; Node.js 24 / pnpm 10; Python / conda for training scripts; Docker for development.</p> <p>This archive captures the v1.0.0 release, delivered for Milestone 3 of the euROBIN 3rd Open Call Technology Exchange Programme (Sub-Grant Agreement euROBIN_3OC_8, project "Enhancing AI-Driven Robotics Through High-Fidelity Synthetic Data for Simulation-Based Learning"). Hosting Technical Partner: INRIA (Serena Ivaldi). The MS3 deliverable was reviewed and approved by INRIA on 30 April 2026.</p> <p>The accompanying SyntetiQ stack components are archived on Zenodo under DOIs 10.5281/zenodo.19818731 (IsaacSimApp — synthetic-data generator) and 10.5281/zenodo.19819084 (RoboLab — TIAGo data collection). The continuously updated source is on GitHub at https://github.com/syntetiq/syntetiqdaas.</p> <p>Released under the Apache License 2.0.</p> <p>Funded by the European Union — euROBIN, the European Robotics and AI Network (Horizon Europe Grant Agreement 101070596).</p> |
| title | SyntetiQ DaaS — Dataset and Model Lifecycle Platform for AI Robotics (euROBIN MS3, INRIA-reviewed) |
| topic | euROBIN euROBIN_3OC_8 SyntetiQ synthetic data MS3 INRIA-reviewed dataset management model training object detection YOLO PyTorch OroPlatform Symfony Omniverse DaaS |
| url | https://doi.org/10.5281/zenodo.19818727 |