Zero-config entity resolution feeding a durable identity layer: messy records from any source become stable golden entities, a Customer 360 with provenance, merge/split and audit. Fellegi-Sunter beats hand-tuned Splink. Arrow-native/Rust, 250M rows in 11.2 min. Python + edge TypeScript (WASM), SQL-native in Postgres & DuckDB, 97 MCP tools + REST.
Datagrunt is a Python library designed to simplify the way you work with CSV, Excel, Parquet, and PDF files. It provides a streamlined approach to reading, processing, and transforming your data into various formats, making data manipulation efficient and intuitive.
Frontend & BFF (Backend for frontend) for Olake. This includes the UI code and backend code for storing the configuration of sync and orchestrating it.
Dex is the agent-native analytics engineering toolkit. Point it at your warehouse and your dbt project. It learns the landscape, authors your transformations, and tells you exactly what to fix when the schema drifts. Built for analytics engineers and data engineers who want more out of their coding agent.
Deterministic file observation for pipelines — one read-only pass over a directory emits a reproducible JSON manifest of every file's type, metadata, structure, and provenance.
Python SDK for the VGI (Vector Gateway Interface) protocol — host DuckDB scalar, table, aggregate, and table-in-out functions in an external worker over Arrow IPC.
Synthetic test data that hits the numbers you declare, exactly. Multi-table with verified foreign-key integrity, deterministic, no model in the data path. Python + MCP server.
ETL / ELT / Reverse ETL Framework powered by DuckDB, designed to seamlessly integrate and process data from diverse sources. It leverages Markdown as a configuration medium, where YAML blocks define metadata for each data source, and embedded SQL blocks specify the extraction, transformation, and loading logic.
TypeScript SDK for the VGI (Vector Gateway Interface) protocol — host DuckDB scalar, table, aggregate, and table-in-out functions in an external worker over Arrow IPC.
Lint the documentation & metadata quality of VGI (Vector Gateway Interface) data workers — descriptions, column comments, tags, and example queries — with a quality score, per-version baselines, and agent-friendly output.
The Lakehouse Engine is a configuration driven Spark framework, written in Python, serving as a scalable and distributed engine for several lakehouse algorithms, data flows and utilities for Data Products.
Go SDK for the VGI (Vector Gateway Interface) protocol — host DuckDB scalar, table, aggregate, and table-in-out functions in an external worker over Arrow IPC.