About

The dependence structure of intelligence.

Copula Lab is a provider of expert-built benchmarks, high-quality data, and real-world environments for frontier models and vertical agents. We are registering in Shanghai with an overseas entity coming in Q2 2026.

Mission

Close the gap between model capability and expert-level work.

The path to AGI runs through two bottlenecks: compute and data. Compute has attracted enormous attention. Data — specifically the kind of high-quality, expert-grounded data that teaches models how specialists actually reason — has not kept pace.

Surge AI, Mercor, and their peers have validated overseas that frontier models need real domain experts to educate, align, and evaluate them. The standard annotation pipeline, staffed by general workers, can no longer move the needle on the models that matter.

We are building the infrastructure that closes that gap: expert networks, data pipelines, evaluation environments, and benchmark suites designed by people who understand what frontier models actually need.

Why Copula

Sklar's theorem, 1959.

C(u₁, u₂) = F(F₁⁻¹(u₁), F₂⁻¹(u₂))
where F₁, F₂ are marginal CDFs
and C is the copula joining them.

In statistics, a copula is the function that joins separate marginal distributions into a true joint distribution. It captures the dependence structure between variables — how they move together, especially at the extremes.

Model capability and real-world task performance are two marginals. Most benchmarks measure each in isolation: how well does the model score on the test? How does it perform in deployment?

We model the dependence between them. That means measuring not just average performance, but the tail behavior — the scenarios where models break in ways that matter for real use.

In linguistics, a copula is the linking verb — "is," "are," "be" — the word that connects subject to predicate. The company's name holds both meanings at once.

Roadmap

Where we are and where we're going.

Phase 1

Now — 3 weeks

Release VLM Benchmark and Office Workflow Benchmark
Build social presence across domestic and international channels
Source first cohort of domain experts
Complete company registration (Shanghai)

Phase 2

4–7 weeks

Reach out to domestic base model teams with benchmark results
Establish first expert collaboration and data pipeline
Publish model comparisons on proprietary benchmark cases
Establish overseas entity

Mid-term

3–6 months

Standardized expert sourcing, data construction, and evaluation pipeline
Packaged delivery SKUs — not bespoke case-by-case
Validation mechanism on open-source models (Qwen-class)
2–3 key accounts with ongoing data partnerships

Long-term

Beyond

Extend expert organization model to World Models and embodied AI
Serve next-generation models as multimodal and causal reasoning mature
Build the infrastructure layer that scales with the frontier

Company

Status: Registering in Shanghai
Overseas entity: Coming Q2 2026
Contact: hello@copulalab.com

We work with frontier labs, research groups, and AI companies that take evaluation seriously. If that's you, we'd like to talk.

Talk to us →