专为 AI 蛋白设计团队打造的湿实验验证 CRO。你的序列，隔离、加密、绝不训练，数周内拿回可信的实验判定。
A wet-lab validation CRO built only for AI protein-design teams. Your sequences stay isolated, encrypted, never trained on, and validated in weeks.
序列即核心 IP。项目物理与数据双隔离，默认 NDA，绝不混线，绝不用于任何模型训练，交付后按约销毁。
Sequences are your core IP. Per-client isolation, NDA by default, never co-mingled, never used to train any model, destroyed on request.
你提交的是文库，不是单条。96 孔并行加 BLI 批量筛，收 FASTA / PDB，回传可直接喂回训练的结构化数据。
You submit libraries, not singles. 96-well parallel plus BLI screening, FASTA / PDB in, training-ready structured data out.
序列进、结合数据出，2 到 3 周。失败漏斗在最便宜的环节筛掉废设计，哪条死了我们主动告诉你。
Sequence in, binding data out, 2 to 3 weeks. The failure funnel kills dead designs cheap, and we tell you which ones so you stop paying.
标准化的数据管理流程，全链路留痕、可审计、可复核。结合亲和力至少两种正交手段交叉验证，数据经得起投资人与药企质疑。
A standardized data-management flow: every step logged, auditable, reviewable. Binding cross-checked by two orthogonal methods, so data survives investor and pharma scrutiny.
不经实体实验，AI 的结构与结合预测无法向投资人、药企、监管交付可信证据。
Without a physical experiment, AI's predictions aren't credible to investors, pharma, or regulators.
合格的蛋白湿实验意味着高昂设备与数年积累，早期团队负担不起。
A capable protein wet lab means heavy capex and years, which early teams can't carry.
设计到构建到测试的循环越快，模型进步越快。慢验证拖慢整个公司。
The faster the design build test loop, the faster the model improves.
从表达开始层层设卡：表达、折叠、结合、功能、成药性。首发聚焦第一至第三层。
The challenge starts at expression: fold, bind, function, develop. We launch with Tiers 1 to 3.
FASTA / PDB
层级 · 通量tier · throughput
并行 · 快筛parallel
正交验证orthogonal
结构化数据structured data
de novo 结合子、抗体、酶设计，交序列，数周后拿回能喂回训练的验证数据。
Binders, antibodies, enzymes. Send sequences, get training-ready data back in weeks.
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