Approximate Labs

Boulder, CO

Independent research into the efficiency of reasoning.

Studying the efficiency gap between human and machine reasoning. We build benchmarks, tools, and architectures to close it.

Research Log

Date

Pencil Puzzle Benchmark

March 2, 2026
Evaluation

62,231 puzzles. 94 types. 51 models evaluated. Deterministic step-level verification.

Lab History (2022–2024)

TabLib
Dataset

The world's largest open-source dataset of tabular data. 627M tables extracted for training Large Data Models.

HuggingFace ↗
Sketch
Tool

An AI code-writing assistant for pandas that understands data context via approximate summarization algorithms.

GitHub ↗
Julyp
Product

Data-focused AI assistant (formerly Tabby Chat and Julyp) backed by on-demand Jupyter Lab environments with dynamic installs, cached data pipelines, dashboards, and full iframe/canvas rendering.

TableGen
Product

Experimental smart spreadsheet where each cell runs an agent with row and column context. Agents execute in parallel to fill tables and enable fast data manipulation.

Founder | Principal Investigator

Justin Waugh