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Research participant marketplace that gives AI teams and academics fast access to verified, screened human data and feedback.
Data-labeling and RL data platform supplying training data, environments and evaluation for frontier AI labs and enterprises.
Marketplace that matches vetted human experts with AI labs to produce training data and model evaluations.
Long-standing provider of human-labeled, expert-validated training data and model evaluation services for building frontier AI.
OCR and document-conversion tools that turn PDFs, images and handwriting (math, chemistry, tables) into editable text and Markdown.
No public pricing
No public pricing
No public pricing
No public pricing
No public pricing
- ✦300,000+ verified, screened participants
- ✦300+ audience targeting filters
- ✦Representative and quota-based sampling
- ✦API and no-code survey tool integrations
- ✦AI-powered participant quality monitoring (Protocol)
- ✦Managed services with dedicated project teams
- ✦Access to vetted domain experts
- ✦Data labeling across modalities
- ✦RL environments and reward signals
- ✦Custom model evaluations and benchmarks
- ✦Human preference/annotation from an expert network
- ✦Recursion RL platform for enterprise agents
- ✦Robotics data (video, trajectories)
- ✦Curated roles across many expert domains
- ✦Expert vetting and matching to AI projects
- ✦Hourly-paid contract work for specialists
- ✦APEX benchmarks and off-the-shelf datasets
- ✦Enterprise data partnerships and evaluations
- ✦Daily payouts to contributors
- ✦Frontier alignment data (RLHF, SFT, red teaming)
- ✦Speech and audio data
- ✦Multimodal / VLM annotation
- ✦Physical AI data (LiDAR, robotics, sensor fusion)
- ✦Model integrity, bias and hallucination audits
- ✦1M+ vetted contributors, 500+ locales
- ✦SOC2 and ISO 27001 certified
- ✦OCR for math, chemistry, tables and handwriting
- ✦PDF and image to Markdown/text conversion
- ✦Snip app and Chrome extension
- ✦Convert and Files APIs for developers
- ✦Secure Conversion Service for high-volume enterprise use
- ✦Mathpix Markdown format
- →Collecting human preference data for RLHF or model evaluation
- →Running academic behavioral or market research studies
- →Sourcing domain-expert data for specialized AI benchmarks
- →Building training and evaluation datasets
- →Post-training and RLHF for models
- →Benchmarking model capability
- →Training enterprise specialist agents
- →Source expert human data for AI training
- →Run domain-expert model evaluations
- →Find paid remote work as a domain specialist
- →Build custom datasets for AI labs
- →Source training data for AI models
- →Evaluate and benchmark models
- →Annotate multimodal and sensor data
- →Run safety and bias audits
- →Digitizing handwritten math and technical documents
- →Converting PDFs to editable Markdown
- →Making documents accessible and searchable
- →Building OCR into applications
- →Preparing training data for language models