Alternatives to Klavis AI

Snorkel AI builds expert-curated training data and runnable eval environments that fix where frontier models and agents break.

Labelbox builds Reinforcement Learning environments frontier labs train on and background agents engineering teams hand their backlog to.

Training data, RL environments, and red-teaming for LLM and computer-use agent teams

GameEngineBench scores frontier AI models on real UE5 game-engine programming tasks, not static coding puzzles.

AfterQuery builds expert reasoning training data — SFT, RL rubrics, agent environments, and computer-use trajectories for frontier models.

Mercor connects AI labs with vetted domain experts to build training data, evals, and APEX benchmarks for frontier models.

Free browser tool from Google for training image, sound, and pose classifiers with no code and no account.

PublicAI is a Web3 data infrastructure platform that pays a global workforce in crypto for multi-modal annotation, coding trajectories, and LLM benchmarks.

Load, stream, and preprocess training datasets in one line of Python — open source, Arrow-backed, Hub-native

Prodigy is a downloadable Python annotation tool for building training and evaluation data for custom AI, ML and NLP models.

Synthetic data generation for computer vision that ships photorealistic, auto-annotated training sets on demand.

Free MIT Python CLI that turns AI coding assistant chat history into one normalized JSONL dataset for fine-tuning and analytics.

Licensed conversational audio datasets for training speech and omni-models, with samples in 48 hours.

Generate LLM training datasets with DAG topic graphs and real sandboxed tool-calling traces

Hub recruits the physical world to capture egocentric, teleoperation, hand-tracking and tactile training data for embodied AI.

Enterprise dataset management platform for AI training teams

Applied AI for aviation: pilot-controller training datasets, the Y4 Aviation Understanding Model, and real-time runway incursion risk detection.

Sureform turns your operational data into a licensable AI training asset that pays you per deal

Human-recorded computer-use datasets that teach AI agents to operate real software the way people do.

Mundo AI builds culturally-aware audio and video training data, evaluations, and applied research for teams working on perceptual AI.

BioStack Platforms supplies structured clinical datasets and RL environments for healthcare AI teams.

Ocular delivers full-duplex conversational speech data and benchmarks frontier STT models on real-world audio.

Private-deployment data annotation platform for multimodal AI training, from BasicAI.

Licensed audio datasets for teams training speech recognition, translation, and voice interaction models

Custom audio datasets for training and evaluating voice AI, scoped to your model's spec.

Synthetic data cloud for computer vision: physically-based rendering that generates annotated, multi-sensor training imagery.

Velvet sources, verifies, and delivers curated video datasets so AI labs can train interactive and world models with spatial reasoning.

Open-source, no-code system from IBM Research for labeling text and training custom text classifiers without AI expertise.

Physical AI data infrastructure that turns real-world task capture into multimodal robot training datasets

Open-source data labeling and AI evaluation across every data modality, self-hosted.