3. Data, Science & AI

Provides advanced document search with BM25, semantic vectors, and hybrid retrieval for precise technical queries and knowledge base management.

Builds type-safe LLM applications using DSPy.rb, a Ruby framework for programmatic prompt engineering with signatures, modules, and optimization.

Enables advanced AI model evaluation through LLM-as-a-Judge techniques for quality assessment, bias mitigation, and output comparison.

Optimizes AI agent performance by compressing conversation history to reduce memory usage and token consumption in long sessions.

Optimizes and designs production-ready prompt templates for LLM interactions to improve output quality and reliability.

Designs strategic metrics dashboards with North Star Metrics, AARRR framework, and role-specific data infrastructure for data-driven business decisions.

Analyzes customer data to reduce churn through cohort analysis, at-risk identification, and generates HTML reports with retention curves and implementation roadmaps.

Enables pattern discovery and insight generation within Knowledge Graphs, helping users explore entities, connections, and potential applications.

Directly launches external AI CLIs (Gemini, Codex, Claude) with role-based prompts and file references, bypassing MCP server.

Resolves duplicate entities in Knowledge Graphs by identifying matches and merging them, supporting automatic and user-confirmed merges for high and medium confidence cases.

Bootstraps knowledge graphs from video transcripts by extracting entities and relationships for analysis and search.

Guides users through transcribing video/audio files and YouTube URLs using GPT-4o for accurate media-to-text conversion.

Validates datasets for Unsloth fine-tuning, analyzes tokens, calculates Chinchilla optimality, and prepares data for training.

Manages local GPU training workflows including CUDA validation, GPU selection, progress monitoring, and checkpoint handling for machine learning models.

Launches and monitors Hugging Face model fine-tuning jobs on cloud GPUs with optional WandB integration for AI training workflows.

Generates professional model cards and uploads fine-tuned machine learning models to Hugging Face Hub with comprehensive documentation.

Creates Unsloth-based training notebooks and scripts for configuring fine-tuning parameters and setting up SFT/DPO/GRPO workflows.

Validates production readiness of Vertex AI Agent Engine deployments across security, performance, compliance, and best practices with weighted scores and recommendations.

Automates data cleaning, transformation, and validation for machine learning pipelines.

Executes clustering algorithms (K-means, DBSCAN, hierarchical) to identify natural groupings in datasets for data analysis and pattern recognition.

Analyzes blockchain data to track whale movements, token flows, and network activity for cryptocurrency market insights.

Real-time scanning of cryptocurrency exchanges and DEXs to identify and alert on profitable arbitrage opportunities.

Automates database schema comparison and synchronization for efficient data management.

Queries and analyzes blockchain data including blocks, transactions, and smart contracts for insights.