We are pleased to announce that Quark Labs, an AI startup recently emerging from stealth, has selected Bit Refinery as the infrastructure foundation for its platform. Quark Labs builds trusted automation for document-driven decisions in regulated industries, and will run its custom inference workloads on our private, single-tenant GPU infrastructure in Denver, Colorado.
The partnership directly addresses one of the most pressing questions for any AI startup serving regulated customers: where, and how, their models actually run. For Quark Labs' customers in finance and healthcare, the answer cannot be "a shared GPU somewhere in a hyperscaler region" — it has to be dedicated hardware, in a known U.S. jurisdiction, with no model-provider telemetry and no per-token billing that scales unpredictably with their own customer growth.
Why this matters for regulated AI
The AI infrastructure market has been dominated by two options: hyperscale cloud GPU rentals (priced per-GPU-hour, with significant egress fees and shared scheduling) and consumer-grade GPU clouds (lower cost, but typically multi-tenant and lacking the compliance posture regulated buyers require). Neither answer is acceptable to a buyer whose auditors will ask which physical hardware their workloads ran on.
Bit Refinery's private GPU cloud sits between those extremes — dedicated NVIDIA hardware on bare metal, single-tenant isolation, fixed monthly pricing, and zero egress fees, deployed in Tier 3 data centers in Denver and Seattle. For Quark Labs, that model translates directly into customer trust. Their platform never sends customer data to a third-party model provider's API. Inference runs on dedicated GPUs that no other tenant shares. There is no telemetry pipeline back to a foundation-model vendor. Customer data, fine-tuned model weights, and audit logs all stay within infrastructure we own and operate.
"Quark Labs is exactly the kind of company we built our private GPU infrastructure for. They're serving customers whose data cannot leave a controlled environment, whose compliance teams need to know precisely which physical hardware their workloads ran on, and whose business model can't absorb the variable per-token economics of a hyperscale API."
— Mike George, VP of Operations, Bit Refinery
What Quark Labs does
Quark Labs builds AI-powered automation for the document-heavy workflows that drive consequential decisions in regulated industries — finance, insurance, and healthcare. Its document extraction intelligence platform transforms complex documents into structured knowledge that powers automated workflows, compliance checks, and cross-document insights. The platform handles intricate PDFs, embedded images, PHI & PII, and other sensitive data that traditional tools find too expensive or error-prone to parse at scale — delivering trusted automation with built-in compliance and full auditability.
Co-founded and led by CEO Vishal Singh, Quark Labs recently emerged from stealth to address a gap in the market: organizations in regulated industries cannot adopt off-the-shelf foundation-model APIs without conceding control over where their data lives and how it is processed.
"Our customers operate in industries where 'the cloud' isn't a neutral answer — it's a question their auditors, their security teams, and their regulators will ask. Bit Refinery gave us dedicated NVIDIA hardware, a clear U.S. data-center footprint, predictable monthly economics, and an engineering team that actually picks up the phone. That combination simply isn't available from the hyperscalers at our stage, and it lets us tell our customers exactly where their data lives and what it's running on."
— Vishal Singh, CEO and Co-Founder, Quark Labs
The infrastructure underneath
Quark Labs' inference workloads run on our private GPU cloud — dedicated NVIDIA GPUs in our Tier 3 Denver, Colorado facility, single-tenant bare metal with no virtualization layer and no third-party model API in the request path. Each deployment includes fixed monthly pricing in place of per-token billing, and zero egress fees in place of the variable bandwidth costs that make customer growth feel like infrastructure punishment.
The combination — dedicated hardware, a known U.S. jurisdiction, predictable economics, no telemetry back to a foundation-model vendor — is what makes the platform credible to the compliance teams who will not accept a shared-tenancy answer.
Joint go-to-market
We are collaborating with Quark Labs on shared content, joint case studies, and industry-event participation. A dedicated partner page at bitrefinery.com/partners/quarklabs covers the technical and commercial detail of the relationship — including the architecture, the FAQ that regulated-AI buyers actually ask, and the compliance posture of the infrastructure underneath.
If you are building AI for regulated customers and the data-residency, isolation, and pricing questions are blocking you, get in touch. The same infrastructure that powers Quark Labs is available to you.