Artifact
The internet is exhausted. Machine intelligence must now be taught directly — by human intelligence.
Artifact is a data research company with a mission to push machine intelligence further beyond. We partner with researchers at the frontier AI labs, leading enterprises building models, and other data firms.
Our current focus is building RL environments and running expert human data projects that are large, operationally complex, and aimed at the capabilities with real economic value.
Services
Training Data
SFT: Expert demonstrations of real engineering work — repository-scale changes, debugging, and structured reasoning.
RLHF: Preference data that teaches models the difference between code that runs and code that ships.
Off-the-Shelf: Pre-built expert datasets — thousands of hours of expert reasoning spanning RL environments, coding, and core capabilities, ready to use today.
Evaluation Infrastructure
RL Environments: Outcome-verifiable coding environments that test agent behavior under realistic conditions.
Rubrics & Verifiers: Objective scoring systems that separate expert-level code from plausible-looking output.
Human Evaluation: Senior-engineer judgment on correctness, quality, and safety — beyond gameable benchmarks.
Red Teaming: Adversarial testing that surfaces vulnerabilities and failure modes before deployment.
Specialized Domains
Expert Sourcing: Data from working senior engineers — real expertise, not approximations.
Languages & Stacks: Mainstream and long-tail programming languages, frameworks, and legacy systems.
Agentic Data: Computer-use and tool-use trajectories for models that do more than autocomplete.
Internationalization: Data in 70+ languages that captures grammar, idioms, and cultural context. Not translation — localization.
Multimodal: Vision, audio, and video training data for models that need to understand beyond text.
Consulting
We audit existing datasets, redesign annotation processes, and build the QA pipelines that commodity vendors can't. For labs and other data firms:
Third-Party Review: An unbiased, independent review layer for benchmarks, datasets, and pipelines — whether you're buying data or selling it.
Pipeline Buildout: We help data firms stand up human data and QC pipelines, built on what we've learned running our own.
Workforce Overflow: When buyer appetite outruns your capacity, our expert workforce plugs in so you can keep up.
Working With Us
Our team comes from Scale, Mercor, Uber, Microsoft, Northwestern, CMU, & more. We ship under 3% defects against an industry reality of 10–40% — with audits and full chain of custody on every batch.