Post-training data / intelligence infrastructure
Many minds. Better intelligence.
VoltAI builds post-training data, real-world environments, and evaluation infrastructure for frontier AI.
At a glance
1,000+
Domain specialists
09
Core domains
06
Data product forms
01
Production platform
01 / Core capabilities
Six capabilities for the full model improvement loop
More than data delivery: from real problems to evaluation and continuous iteration.
Expert Data
高难度专业问答、分步推理、偏好反馈与验证标签
Expert Network
任务设计、专业审核、标准制定与质量仲裁
Real-world Data
合规获取真实工作流、过程记录与复杂任务数据
RL Environments
工具接口、状态转换、成功条件与可重现回放
Visual Data Pipeline
任务管理、专家审核、质量验证与生产迭代
Benchmark & Eval
高难度 Benchmark、Verifier 与模型能力诊断
02 / Domain coverage
From code to the real world
Nine domains, grounded in real workflows and complex tasks.
CODING
Repo / Terminal / Agent
FINANCE
投研 / 风控 / 建模
LEGAL
条款 / 检索 / 推理
MEDICAL
循证 / 指南 / 专业审核
INDUSTRY
制造 / 运维 / 工艺
AGRICULTURE
农情 / 农艺 / 决策
ARTS
创意 / 审美 / 设计评价
SCIENCE
科研推理 / 实验 / 论文
MULTIMODAL
图像 / 视频 / 语音 / 图表
03 / Data product matrix
From static knowledge to executable, verifiable signals
04 / Model improvement loop
Let verified feedback drive the next task
From real-world tasks to training feedback: a verifiable data × model improvement flywheel.
Real-world tasks
Expert knowledge
Data & environments
Model rollout
Verifier & evaluation
Failure analysis
05 / Partnership
Start with a model gap. Build something measurable.
Begin with a focused pilot, validate the signal, then scale into a durable improvement loop.
Discuss your task