Agents
Builds a polished Excel financial model for any company. Give it a public company ticker (data pulled automatically from Yahoo Finance and SEC EDGAR) or a private company spreadsheet, and it outputs a fully formatted .xlsx with a 3-statement model (Income Statement, Balance Sheet, Cash Flow) plus DCF valuation — 5 years historical, 5 years projected, WACC build-up, and a sensitivity table.
This agent helps Python teams using the Anthropic or OpenAI SDK safely cut LLM spend without risking regressions. With zero code changes, it maps call sites and runs your test scenarios to rank token waste from missed prompt caching or heavy model tiers. It tests fixes in isolated git worktrees, enforcing a strict "do-no-harm" gate that reverts any patch failing to preserve behavior. It delivers a clear savings audit that converts into verified, behavior-preserving code patches upon opt-in.
A full analysis pipeline that turns a dataset into a finished report, not just charts. Hand it a CSV, Excel, Parquet, or JSON file and it cleans the data, scores its quality, runs EDA, and where the data supports it, trains a prediction model with SHAP attribution and a backtested forecast. You get a trust score, ranked findings, and recommendations as a Word doc, an interactive HTML report, and an optional PowerPoint deck. The numbers come from code, so they stay consistent, never invented.