Aptan.ai provides end-to-end AI data services tailored to medical robotics, enabling the development of intelligent, safe, and clinically aligned robotic systems. Our solutions are powered by deep domain knowledge, precision annotation pipelines, multi-modal sensor alignment, and rigorous validation frameworks to support the next generation of AI-driven surgical, diagnostic, and assistive robots.
What We Provide
Robotic Vision & Surgical Scene Annotation
- High-precision labeling of endoscopic, laparoscopic, and surgical microscope video feeds
- Instrument detection, tracking, and pose estimation (6-DoF, keypoints, bounding boxes)
- Tissue segmentation and anatomy labeling for robot-aware surgical navigation
- Annotation of surgical phases, hand–instrument interaction, and operative events
Sensor & Telemetry Data Labeling
- Structuring data from LiDAR, depth cameras, force sensors, IMUs, and robotic joint encoders
- Annotation of kinematic signals for motion modeling and reinforcement learning
- Labeling haptic feedback, force thresholds, collision events, and manipulation intent
Robotic Control & Motion Dataset Engineering
- Frame-by-frame motion labeling for surgical tool articulation and robotic arm coordination
- Generation of training datasets for grasping, suturing, cutting, cauterization, and retraction tasks
- Demonstration trajectory labeling for imitation learning and autonomous skill acquisition
Clinical Workflow & Context Alignment
- Labeling of procedure protocols, surgeon actions, safety constraints, and robotic decision logs
- Structuring OR (Operating Room) workflow data for real-time robotic assistance
- Annotation of surgeon preferences, ergonomics, error patterns, and correction pathways
Simulation & Synthetic Data for Robotics
- Creation of annotated synthetic surgical environments for training robotic agents
- Labeling of virtual anatomy, tool behavior, and robot motion policies
- Domain adaptation support to bridge simulated and real surgical scenes
Safety, QA & Clinical Validation
- Surgeon and roboticist-led dataset review and verification
- Multi-layer QA checks for spatial accuracy, temporal consistency, and safety correctness
- Secure, encrypted, and compliance-first dataset delivery for regulated robotics AI systems
- Audit-ready labeling trails and validation reports
Key Use Cases
- AI-driven surgical instrument autonomy
- Robotic skill learning via imitation and reinforcement learning
- Real-time anatomy-aware surgical navigation
- Collision detection and safety monitoring
- Human-robot coordination and assistive decision support
- Intelligent motion planning for surgical and rehabilitation robots
With clinically validated data and scalable annotation pipelines, Aptan.ai empowers medical robotics AI systems that surgeons trust and patients depend on.