3. Data, Science & AI

Enables semantic search and RAG with persistent vector-based memory storage for knowledge retrieval across sessions.

Optimizes AI context management and RAG performance using a hierarchical memory architecture (short-term, long-term, episodic) based on Mem0 research.

Guides athlete video analysis for CMJ and drop jump using pose detection, kinematics, and kinemotion CLI for troubleshooting and execution.

Validates location data, ensures spatial coherence, and creates cartography for post-apocalyptic world mapping and geographical relationship analysis.

Specializes in user behavior tracking, usage analysis, and conversion optimization through data-driven insights for product improvement.

Instrument business operations with KPI metrics for charges, invoices, and payments, enabling SLI/SLO monitoring and lifecycle tracking for business process observability.

Creates Home Assistant graphs and visualizations for sensor data, including time ranges, multiple sensors, and aggregations to build energy/climate dashboards.

Builds LLM applications including chatbots, RAG pipelines, and agents via a visual workflow platform with multi-LLM support and Docker/Kubernetes deployment.

Ensures temporal consistency and prevents contradictions within the SyV timeline, maintaining the 2178 perspective.

Guides implementation of ClickHouse materialized views for real-time data aggregation, transformation, and streaming analytics pipelines.

Enables construction, deployment, and management of multi-agent AI systems using the Agno framework.

Maps Lotus Notes reference database dependencies, lookups, and cross-database relationships for orphan handling and synchronization planning.

Converts Lotus Notes rich text fields to HTML, Markdown, and plain text while preserving formatting and embedded media for system migration.

AI-powered engine analyzing content quality using 176 predefined patterns and delivering actionable improvement proposals.

Provides a modular graph-based RAG system for reasoning over private datasets using Microsoft GraphRAG, enabling efficient information retrieval and generation.

Analyzes Lotus Notes NSF database structure, including data models, views, forms, and relationships to support migration and schema understanding.

Framework for temporal knowledge graphs in AI agents, enabling dynamic context engineering for enhanced agent capabilities.

Optimizes ClickHouse queries for speed by refining primary keys, indexes, partitioning, and query patterns in columnar OLAP workloads.

Ethical web scraping tool for extracting structured data from multiple pages with pagination support and export to CSV/JSON/Markdown.

Extracts structured entities from unstructured text using LLMs with source grounding, supporting medical notes, clinical reports, and long documents with visualization.

Orchestrates MacroFlow as a flow network for dynamic coordination of AI models and workflows.

Provides validation patterns for ClickHouse and Kafka data pipelines, including producer/consumer validation, error streaming, idempotency, and schema evolution.

Exports and analyzes Jira issues with flexible filtering, supporting multiple formats for data analysis and metrics tracking.

Transcribes handwritten research notes from PDFs or photos into structured markdown, applying formatting, generating metadata, AI summaries, and appending quotes to a central file.