January 2026 (Month: 2026-01) – Key accomplishments for Supervisely/docs: - Key features delivered: - Documentation Improvements: consolidated updates covering labeling with AI, Volume Interpolation, and YOLO26 guidance; improved navigation, readme readability, and external usage guides. - Model Benchmark Feature: introduced a benchmarking capability to generate a comprehensive performance evaluation report during neural network training. - Major bugs fixed: - Documentation navigation and link integrity: fixed incorrect and relative links, removed unnecessary references, and adjusted section ordering to improve reliability and user experience (supporting commits include link fixes, ordering changes, and readme updates). - Overall impact and accomplishments: - Improved developer onboarding and user onboarding through clearer docs and guided workflows. - Enabled standardized performance evaluation of models during training, aiding benchmarking and comparison. - Increased maintainability and consistency across the docs repository. - Technologies/skills demonstrated: - Documentation engineering, content strategy, link hygiene, and user-facing guides. - AI/YOLO26 guidance documentation and Volume Interpolation usage. - Model benchmarking integration and reporting.

December 2025 performance summary for supervisely/docs: Delivered media-rich documentation enhancements for 3D Point Cloud Labeling and DICOM Segmentation, focusing on clarity, user guidance, and onboarding efficiency. The primary delivery was documentation quality improvements with embedded media, supported by a targeted commit. No major bug fixes were recorded for this repository during the month.

November 2025: Delivered AI-driven data labeling with interactive models and online learning across modalities, plus Vision Documentation Enhancements (VQA guide and image captioning docs). These initiatives reduced annotation time, improved labeling quality, and provided clearer, more consistent guidance for users. Demonstrated capabilities include AI tooling integration, online learning workflows, and documentation best practices.

June 2025: Deliverable-focused documentation update for the 3D AI Assistant in Supervisely/docs. Published a comprehensive Capability Overview detailing capabilities such as automatic cuboid adjustment, interactive object detection, ground segmentation, 3D cuboid tracking, and geometric feature analysis, with embedded links to relevant videos and research papers. This work enhances customer onboarding and reduces support queries by centralizing capabilities and workflows in the docs. Demonstrates strong technical writing, information architecture, and cross-media linking skills, strengthening the knowledge base and accelerating product adoption.

January 2025 monthly summary focusing on key accomplishments and business impact for supervisely/developer-portal. Delivered an end-to-end 3D to 2D segmentation mask projection tutorial (docs + assets) that guides data prep, LiDAR projection, 2D mask creation via convex hull, and uploading results. Included a new supporting image asset and corrected a minor documentation typo to improve clarity. The feature was implemented via three commits and strengthens onboarding, reproducibility, and developer productivity by enabling teams to reproduce 3D-to-2D workflows within the portal.

December 2024: Delivered substantial documentation enhancements and a new tutorial for 3D point cloud segmentation in the developer portal, focusing on 2D mask guidance and sensor fusion, with improved math notation and KITTI transformation references. Updated documentation formatting and clarifications across point cloud segmentation docs and KITTI references to improve readability and consistency. Strengthened the knowledge base and onboarding experience for developers implementing 3D segmentation workflows.