3. Data, Science & AI

Guides structured extraction of information from diverse document formats, enabling data processing for analysis and integration.

Tracks data lineage and provenance to visualize data flow, dependencies, and impact analysis for data pipelines and transformations.

Provides zero-downtime strategies for production database schema evolution and large data backfills, including batching, verification, and rollback planning.

Analyzes A/B test results with statistical significance to guide data-driven decisions on variant performance.

Provides data-driven insights for customer support teams via dashboards, real-time metrics, and predictive analytics to enhance performance and satisfaction.

Enables AI chatbot integration with LINE platform for Thai market customer engagement, supporting messaging and rich menus.

Provides strategies for implementing database locking mechanisms to ensure data consistency during concurrent operations.

Enables advanced research with complex data analysis and high-level machine learning model development.

Implements A/B testing methodology with statistical significance testing to compare two versions of a variable and determine optimal business metrics.

Primary orchestrator agent managing and coordinating AI workflows within the Oh My Antigravity system.

Creates intuitive data visualizations and dashboards for real-time monitoring and data-driven decision-making.

Provides AI-driven analysis of images and videos for object detection, scene understanding, and content extraction.

Step-by-step guide for integrating YOLOv8 and YOLOv9 object detection models via Ultralytics library for computer vision applications.

Enables AI agents to autonomously detect errors, validate outputs, and refine results through iterative self-correction loops and confidence scoring.

Manages AI agent prompts via versioning, A/B testing, and rollback strategies for reliable iterative development.

Delivers comprehensive statistical analysis for data science applications with Sonnet-tier quality and accuracy.

Extracts YouTube video data including audio, captions, comments, and metadata, with AI-generated summaries and analysis via VidCap.xyz API.

Enables rapid exploratory data analysis for quick insights and initial data understanding with minimal setup.

Comprehensive guide for deploying PyTorch models to production, covering export formats, optimization, and deployment patterns.

Tracks viewer behavior, engagement, and quality metrics for video content, including player events, QoE, watch time, and dashboard visualization.

Provides frameworks and libraries for building autonomous AI agents with tool integration and multi-agent coordination capabilities.

Guides A/B and multivariate experiment design, statistical significance calculation, and data-driven analysis for product optimization.

Provides best practices for securely retrieving and managing Open Finance data including accounts, transactions, investments, and identity information.

Detects and manages schema changes in data pipelines to prevent breakages and maintain data integrity for downstream consumers.