3. Data, Science & AI

Generates and interprets nightly Anviloop scoreboard reports, summarizing status, validity counts, and top failing questions for data-driven insights.

Dispatches independent AI agents to solve multiple concurrent problems without sequential dependencies or shared state.

Creates optimized meta-prompts for Claude-to-Claude pipelines and complex multi-stage LLM workflows, enabling automated AI-driven task execution.

Executes a 4-phase iterative loop to progressively refine search context for complex queries with unknown context gaps.

Validates CSV-based IP geolocation feeds against RFC 8805 standards and industry best practices for data integrity.

Evaluates AI agent systems with LLM-as-judge for nuanced quality gates, measuring component quality beyond binary pass/fail checks.

Manages large context by offloading to filesystem, enabling cross-session state persistence and reducing token usage in LLM applications.

Enables creation, validation, and auditing of autonomous AI agents with isolated execution contexts for robust agent system development.

Generates Codex-ready prompts from natural language, including goals, constraints, and acceptance criteria.

Provides AI-powered natural language processing, text generation, JSON extraction, and image analysis via the Anthropic Claude API for structured data and content tasks.

Provides geospatial services including geocoding, route calculation, and delivery route optimization via Mapbox API.

AI telephone agent for automated outbound calls (sales, appointments, surveys) with call configuration, monitoring, and transcript retrieval for structured data extraction.

Enables database querying, data analysis, and transaction handling using SQLAlchemy 2.0+ across PostgreSQL, MySQL, SQLite, and SQL Server.

Provides persistent data storage across ticket executions using DuckDB for state management, caching, and audit logging.

Provides guidance for managing AI models and providers, including implementation status and icon usage.

Monitors AI reasoning for struggle signals and triggers escalation to deep-thinking agents for complex tasks.

Generates videos from text prompts or images using an AI SDK, supporting asynchronous task management for programmatic video content creation.

Fetches real-time web data via Google Search to ground AI responses with current information.

Visualizes audio frequency and time-domain data in real-time, synchronized with React updates.

Manages AI agent development and operations via kubani-dev CLI, providing health checks, version control, deployment status, and evaluation tools.

Detects statistical anomalies in metrics using z-score and threshold analysis for proactive monitoring and early warnings.

Manages hierarchical memory tiers (working, episodic, semantic) for AI agents to store and learn from observations.

Pre-filters articles via Redis cache to eliminate duplicates and avoid redundant LLM calls, optimizing AI processing efficiency.

Optimizes AI model context windows by summarizing, focusing, and pruning input text to maintain efficiency and relevance.