3. Data, Science & AI

Provides consensus-driven reviews by consulting multiple external AI models (Gemini, Codex, Qwen, GLM-4.7) upon explicit user command.

Deploys and operationalizes AI agents on Databricks with MLflow integration, evaluation frameworks, monitoring, and CI/CD pipelines for production environments.

Analyzes CUDA, CPU, and memory performance benchmarks to identify bottlenecks and generate optimization insights.

Expert guidance for building production-ready AI agents with Databricks Mosaic AI, covering architecture, tool design, and Foundation Model integration.

Provides demand forecasting and inventory optimization tools to manage stock levels and streamline supply chain operations across multiple warehouses.

Generates reproducible code for psychology/cognitive science experiment stimuli from design documents and rendering conventions.

Extracts structured sections, abstracts, and metadata from large documents for data analysis and utilization.

Automates batch processing of bank statement PDFs with checkpointing and progress tracking for resumable ingestion across multiple batches.

Builds production-ready RAG pipelines using LangChain and Qdrant for semantic search, document Q&A, and advanced RAG patterns like HyDE.

Enables the AI to learn from user corrections during a session and update its configuration to prevent future errors.

Guides users in creating, configuring, and utilizing Claude Code subagents and the Task tool for specialized AI agent workflows.

Enables creation, editing, and analysis of spreadsheets with formula handling, formatting, data analysis, and visualization across multiple formats.

Provides persistent context storage and retrieval using semantic vector search and full-text keyword search for project knowledge management.

Analyzes DEX liquidity depth and estimates slippage for MEV trading strategies, enabling optimal swap execution and route selection.

Converts bank statement CSV files into structured transaction data, extracting account details and transaction records for analysis.

Automates bank statement processing by extracting transactions from PDF/CSV, categorizing via AI, and storing in a database while archiving files.

Converts bank statement PDFs into structured JSON transaction data with consistent formatting for seamless integration.

Dynamically creates SQLite interaction tools and leverages peer agent collaboration for advanced data processing and analysis capabilities.

Captures task outcomes and patterns post-completion to enable adaptive skill evolution through feedback mechanisms.

Generates realistic dummy data (text, images, products) for Shopify stores using Shopify Schema inputs, enabling efficient testing and development.

Intelligently manages agent context and detects capabilities to optimize AI agent performance in conversational and task-oriented systems.

Extracts text and converts documents (PDF, DOCX, images) to structured formats with OCR support for scanned content.

Analyzes financial transactions by merchant, amount, and context to assign spending categories with confidence scores and pattern rules.

Converts Nextflow process definitions into Galaxy tool XML format for seamless integration into scientific workflow platforms.