Labelbox records 762,803 monthly visits with -22.8% month-over-month growth and Contact for Pricing pricing. Milk Infrastructure records 0 monthly visits with 0% growth and Paid pricing.
The environments frontier AI trains on, and the agents that do the recurring work
Turn the model traffic you already generate into summaries, experiments, and training data
| Dimension / Metric | | |
|---|---|---|
| Official Domain | labelbox.com | milkinfrastructure.com |
| Pricing Model | Contact for Pricing | Paid |
| Monthly Visits | 762.8K (762,803) | 0 (0) |
| MoM Traffic Delta | -225.17K (-22.8%) | 0 (0%) |
| Primary Market & Share | 🇺🇸 United States (21.9%) | 🌐 Global (—) |
| Direct Visits / mo | 370.02K | 0 |
| User Rating | 4.4 | 4.3 |
| Supported Platforms | Website | Website |
The environments frontier AI trains on, and the agents that do the recurring work
Structured annotation, curation, model evaluation and human-in-the-loop review across vision, language and generative tasks, used to build the training and eval data behind production models.
Recursion agents start on their own from builds, alerts, commits, checkpoints and schedules, then work in the background until the task is finished and reviewable.
Specialist agents cover software engineering, reliability, security, ML research, evals, R&D, product and finance workflows, from flaky test fixes to postmortem drafts and vulnerability patches.
Every agent run is scored by a grader, and graded sessions leave memories, notes and skills that the next session reads before acting, so quality compounds over time.
Turn the model traffic you already generate into summaries, experiments, and training data
Point the official OpenAI SDK at Milk Parlor by changing just OPENAI_BASE_URL and OPENAI_API_KEY; Chat Completions and Responses calls stay exactly as they were.
Parlor returns your model's answer as usual while saving eligible request–response pairs in the background, grouped as tasks under your account's unique ID.
A heartbeat counts saved exchanges without making model calls, and at configurable thresholds a job summarizes topics, tasks, and response times.
Give it a goal and it runs commands, starts cloud models, measures results, and saves what it learns — continuing even after you close the dashboard.
Free / Open-sourceGive your AI agents secure, authenticated access to 1,700+ apps
Free / Open-sourceGive your AI agents secure, authenticated access to 1,700+ apps
SpecialistStreamlines end-to-end computer vision workflows from annotation to model deployment, but lacks Labelbox's general enterprise agent orchestration.
SpecialistStreamlines end-to-end computer vision workflows from annotation to model deployment, but lacks Labelbox's general enterprise agent orchestration.
SpecialistRelies heavily on managed human-in-the-loop workforce services for data validation, offering less self-serve technical tooling than Labelbox.
Free / Open-sourceHigh-trust frontier inference, encrypted end to end
Free / Open-sourceHigh-trust frontier inference, encrypted end to end
The data, evaluations and systems behind AI that has to be right.
Offers robust multimodal annotation and workflow automation, featuring slightly more intuitive data curation pipelines for computer vision teams.
Offers robust multimodal annotation and workflow automation, featuring slightly more intuitive data curation pipelines for computer vision teams.
Free / Open-sourceThe TypeScript framework for building, deploying, and observing AI agents
SpecialistTrack, evaluate, and ship AI models and agents in one connected environment.
SpecialistTrack, evaluate, and ship AI models and agents in one connected environment.
Free / Open-sourceThe universal context engine connecting agents to data, tools, and models
Free / Open-sourceFast Apply and agent-tuned inference for coding agents
Free / Open-sourceFast Apply and agent-tuned inference for coding agents
Specializes in advanced computer vision and physical AI data pipelines, though with a narrower focus than general text-and-image labeling.
Specializes in advanced computer vision and physical AI data pipelines, though with a narrower focus than general text-and-image labeling.
