Index00 / Darcode
StatusOperating
FoundedMMXXIII
LocationRemote · Distributed

Intelligence,
engineered into systems.

A studio and venture group building AI infrastructure, applied ML products, and the operating layer for companies that have to learn faster than the market.

Currently shipping · Live systemsScroll · 01 / 08
§ 02 / Services

Six practices, one team, one operating model.

Darcode is structured as a studio. We embed multidisciplinary teams to design, build, and operate intelligent products — from research-grade prototypes to systems running at production scale.

01 / Research

Applied AI Research

Embedded research squads framing the right problem, the right benchmark, and the model architectures that move them.

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02 / Build

Product Engineering

Full-stack teams shipping AI-native SaaS — from data pipelines to interfaces — under our own playbooks.

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03 / Infrastructure

ML Infrastructure

Training, evaluation, and inference platforms tuned for cost, latency, and the failure modes you don't see yet.

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04 / Studio

Venture Studio

We incubate, co-found, and capitalize companies inside the Darcode umbrella, sharing engineers and infrastructure.

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05 / Strategy

Operator Strategy

For leadership teams: where AI changes the unit economics, the org chart, and the moat — in language a board understands.

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06 / Operate

Run & Maintain

Ongoing operation of the systems we ship — on-call, eval drift, retraining cadence, regulatory posture.

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§ 04 / Capabilities

A working stack, not a deck.

Every Darcode engagement starts with what we already have running. The capability set below is what our portfolio shares in common — and what we'll extend for your problem.

Foundation models
Fine-tuning, LoRA adapters, RLHF.
Evaluation harness
Offline, online, drift.
Retrieval pipelines
Hybrid, graph, rerank.
Agent runtimes
Tool-use, planning.
Inference fleet
GPU, multi-region.
Data foundry
Curate, label, audit.
Guardrails
Policy, safety, redteam.
Product surfaces
Web, API, embedded.
§ 05 / Operating

Numbers we'll have to revise next quarter.

Darcode is small on purpose. Our footprint is measured in shipped systems, not headcount or burn rate.

0M
Inferences / day
Aggregate across our deployed systems, end of last quarter.
00
Production systems
Live across compute, retrieval, and serving layers.
0
Engineers · researchers
One team. No agencies, no offshore, no scaling for its own sake.

Bring us the problem
that won't sit still.

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