3. Data, Science & AI

Enables semantic search over vector embeddings for context-aware data retrieval in AI applications and knowledge systems.

Intelligently routes user queries across multiple AI models including Gemini, Codex, Claude, and Council for optimized response generation.

Enables critical decision-making through consensus of multiple LLMs using the Karpathy LLM Council pattern for enhanced reliability.

Enables advanced vector search, distributed AI system development, and multi-database management using AgentDB's QUIC synchronization and hybrid search capabilities.

Trains reinforcement learning agents using AgentDB, applying three core principles for adaptive decision-making in AI systems.

Optimizes vector search performance in AgentDB for efficient similarity queries in AI/ML applications.

Optimizes vector database performance through quantization, HNSW indexing, and caching strategies to reduce memory and accelerate search for AI applications.

Manages cognitive modes for AI systems, enabling automatic mode selection, epistemic consistency, and prompt engineering optimization within VERIX and DSPy frameworks.

Creates AI learning plugins with AgentDBs, training RL models (Decision Transformer, Q-Learning) to build self-learning agents and optimize behavior through experience.

Extracts structured data from web pages using sequential planning, handling pagination and transforming data for analysis.

Enables the skill to learn from session corrections and patterns, updating its memory for continuous improvement between executions.

Personalized adaptive learning system using AI reasoning and agent database for dynamic educational experiences.

Enables adaptive learning for self-learning agents via a 150x faster vector database with trajectory tracking and memory distillation for optimized decision-making.

Provides persistent memory patterns for AI agents, enabling state retention and context continuity across interactions.

Provides command-line instructions for querying Google BigQuery, including SQL execution, dataset exploration, and result export.

Analyzes contact angles to characterize surface energy and assess hydrophobicity/hydrophilicity of materials.

A library for evaluating and manipulating mathematical special functions, essential for scientific computing and engineering applications.

AI-optimized warehouse slotting engine that enhances operational efficiency by analyzing product velocity and pick frequency patterns.

Integrates supply chain systems and data sources for end-to-end visibility and analytics.

Generates optimized conference schedules using Google OR-Tools CP-SAT solver, handling constraints like speaker conflicts and room assignments from CSV inputs.

Generates optimized conference schedules using constraint satisfaction (TimeFold) from CSV data, handling speaker conflicts, room assignments, and availability constraints.

Analyzes extractables and leachables data from medical devices to ensure chemical safety and regulatory compliance through scientific data processing.

Enables modular workflow design and subgraph composition for LangGraph, facilitating complex LLM agent application development.

Provides a robust library of geometric primitives for computational geometry tasks in software applications.