Compute became collateral faster than anyone learned to verify it.
Silicon Lien is an independent verification and intelligence firm for large-scale compute. We bring the operator’s knowledge of GPU infrastructure, cluster systems, and hardware economics to the lenders, investors, insurers, and rating agencies that now depend on them.
We understand compute infrastructure the way its operators do.
Large fleets are systems, not line items. Our work rests on the disciplines it takes to run them.
Fleet telemetry
Modern fleets emit device-level data as a matter of basic operations: utilization, power draw, thermals, error activity. We know what these signals mean, what they miss, and how they can mislead.
Cluster systems
A GPU’s productive value depends on what surrounds it: interconnect fabric, power contracts, cooling, and the software that keeps utilization high. We evaluate clusters as operating systems of hardware, not inventories.
Hardware lifecycle economics
Depreciation, refresh cycles, generational transitions, and residual value. The distinction between replacement cost and value in use, measured rather than assumed.
Physical verification
Serial-level sampling, site inspection standards, and evidence protocols designed to support lender review, subject to the scope and limitations of a written engagement. Independent measurement points, cross-checked.
Market data
A daily rental-rate series is in development using public GPU marketplaces, with secondary-market coverage planned. Observable evidence for assets usually marked by negotiated schedules.
Counterparty analytics
Demand decomposed by counterparty: whose workloads run on the fleet, whose capital funds the purchases, and how much of the order book stands at arm’s length.
For the institutions on the other side of the hardware.
Pilot engagements for lenders, structured-credit investors, insurers, and rating agencies. Scope and availability are agreed case by case.
Assessment
Pilot deal-time evaluation of compute assets and the systems around them, documented under a versioned methodology and designed for the credit file.
Monitoring
Monitoring programs designed for the life of a facility: independent measurement on an agreed schedule, with defined escalation.
Data & research
Published analysis and price series in development, designed to be maintained continuously rather than assembled per engagement.
Independence is a method, not a claim.
Independent measurement
We rely on cross-checked signals from sources no single party controls. No single party’s self-reported data is intended to be load-bearing on its own.
Versioned methodology
Our methodology is versioned and will be published. Findings state what agreed with what, under which version. Precision about what was checked is the product.
Conflict checks
Before accepting an engagement, we identify and disclose material financial or commercial conflicts relevant to the work. We do not broker transactions or accept compensation contingent on a finding.
Research on the compute economy.
We publish research on compute infrastructure and the markets forming around it; the datasets behind that work are being built now.
GPU Collateral: Building a Verification Layer for Compute Credit
Why compute credit needs an independent, post-close verification layer, and how Silicon Lien proposes to build it. Read the note →
GPU rental price tracking
A daily series sourced from public marketplaces is in development, with secondary-market coverage planned. Ask about early access →
Built by operators.
Silicon Lien was founded by Akshat Kaul, who led Meta’s machine learning data platform, the $1B infrastructure that feeds training for Meta’s models. Before that he built Redfin’s data and machine learning organization.
Silicon Lien’s methods come from the operator’s side of large-scale compute: measurement-first, systems-level, and skeptical of any number that arrives without instrumentation behind it.
For engagements, research access, or a conversation about the current note: