Harvey
服务法律专业人士的AI研究与工作流平台
成立年份2022
国家United States
一级垂类Legal
二级垂类Legal Research
AI Native：confirmed。AI是法律研究和工作流核心 · 官网
1. 商业数据
收入历史
| 口径 | 金额 | 期间 | 属性 | 日期 | 状态 | 置信度 |
|---|---|---|---|---|---|---|
| ARR | $300m | point_in_time | Est. | 2026-05-31 | reported | 0.6 |
融资与估值历史
| 估值 | 类型 | 轮次 | 日期 | 状态 | 置信度 |
|---|---|---|---|---|---|
| $11.0bn | primary_round_post_money | Growth Round | 2026-03-13 | confirmed | 0.95 |
2. 模型与技术路线
| 路线 | 修饰 | 供应商 | 模型 | 关系 | 用途 | 日期 | 状态 | 置信度 |
|---|---|---|---|---|---|---|---|---|
| 第三方多模型 | 法律定制 | OpenAI / Anthropic / Google DeepMind | 未披露 | Unknown | Legal AI | 2026-03-13 | confirmed | 0.95 |
3. 算力与云
| 供应商 | 类型 | 用途 | 日期 | 状态 | 置信度 |
|---|---|---|---|---|---|
| 自建 Agent 运行时 | unknown | cloud_hosting | 2026-03-13 | confirmed | 0.95 |
4. 来源与证据
收入：arr reported · 置信度 0.6
Harvey revenue, valuation & funding · 2026-06-10 · 原始来源
Sacra estimates that Harvey hit $300M in annual recurring revenue (ARR) in May 2026, up from $195M at the end of 2025.
估值：primary_round_post_money confirmed · 置信度 0.95
Harvey Raises Growth Round at $11 Billion Valuation Co-led by GIC and Sequoia · 2026-03-13 · 原始来源
Today we’re announcing that we’ve raised $200M at an $11 billion valuation.
模型：OpenAI / Anthropic / Google DeepMind confirmed · 置信度 0.95
Why Harvey is Multi-Model by Design · 2026-03-13 · 原始来源
Last year, Harvey went multi-model, expanding its platform to incorporate leading foundation models from Anthropic, Google DeepMind, and OpenAI.
算力/云：自建 Agent 运行时 confirmed · 置信度 0.95
Why we Built our own Cloud Agent Infrastructure · 2026-03-13 · 原始来源
We built our own cloud agent infrastructure for a simple reason—our clients needed agents in production now, and meeting their requirements for multi-model flexibility, zero data retention, and cost means owning the runtime they operate on.
技术：multi_model_routing confirmed · 置信度 0.95
Why Harvey is Multi-Model by Design · 2026-03-13 · 原始来源
Harvey’s multi-model architecture provides structural redundancy. If one provider experiences capacity constraints, service degradation, or an outage, Harvey can route work to an alternative model without disrupting the user's workflow.
技术：agent_harness confirmed · 置信度 0.95
Why we Built our own Cloud Agent Infrastructure · 2026-03-13 · 原始来源
We built our own cloud agent infrastructure for a simple reason—our clients needed agents in production now, and meeting their requirements for multi-model flexibility, zero data retention, and cost means owning the runtime they operate on.