R&D lab · Original systems research

We solve the hard problem. We show you the number.

Original algorithms and data structures, from a ransomware detector at 0.966 AUROC on unseen hardware to a capsule-endoscopy triage system evaluated on 47,161 real frames. We publish what we solved and how much better the result is.

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SHARD Gateway · real GPU evidence

Proven on real hardware, not projections.

Every number below is from a real, repeatable GCP run against a real vLLM instance.

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30.5×

Peak SLO-goodput improvement under aggressive overload, real GCP run

Real CUDA out-of-memory crashes found, across every phase and model tested

30/30

Idle-phase response checks matched baseline vLLM byte-for-byte, across all models

110%

Yi-9B throughput through the Gateway at realistic load, versus raw vLLM (1.400 vs 1.269 req/s)

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What we can build for you

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Research & Products

SHARD Gateway and SHARD Context, our AI infrastructure products.

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Odoo ERP

Implementation, migration, and custom modules for your ERP.

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Web & App Development

Custom web and Android applications, built to be maintained long-term.

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Business Development (BDE)

A dedicated business development function, run on your behalf.

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AI Development

Custom AI/ML development and evaluation pipelines for your workload.

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SHARD Gateway

SHARD Context

0.966

AUROC detecting ransomware on hardware never seen in training, from disk metadata alone (PRISM-CVM, under review)

47,161

Endoscopy frames processed in a single real evaluation run, on a public clinical dataset

Deployable AI infrastructure products, each built on original algorithms and data structures

Simulated results. Every number we publish comes from a real, executed run

Research

What we solved. How much it moved the number.

No simulated benchmarks, no back-of-envelope estimates. Real runs, on real hardware and real data.

All research

Patent filed, manuscript in preparation

SHARP-Core

High-performance data infrastructure

Systems that need fast exact lookups, priority-ranked retrieval, and ordered range queries over the same data, under a hard resource budget, usually have to choose between one general-purpose structure that's mediocre at all three, or three separate systems that drift out of sync with each other. And when a budgeted index refuses an insert, it rarely records whether the budget or the structure itself was the cause.

The admission check costs 5–10 ns per put-heavy operation under identical dispatch, and at most 2 ns on read-mostly workloads.

Original research

SHARP-WCE

Medical imaging

A single capsule-endoscopy study produces 50,000–80,000 images per patient, and reviewing that volume is the acknowledged bottleneck of the diagnostic method. The open question isn't just which frames look abnormal, it's how to retain, rank, and triage that volume under real memory and storage limits without losing a defensible record of every decision.

Which of two comparably-trained scoring models feeds the system swings the flagged-for-review rate by more than 40 percentage points, a dependency our system makes visible and measurable instead of hiding it.

Original research

SHARP-Serve

AI inference infrastructure

Production LLM inference clusters running above roughly 60% memory utilization face a scheduling problem, not a modeling one: when a request's cached context has been evicted to slower memory, the system has to decide whether recovery can finish before that request's deadline, before admitting it to the next processing batch. Existing schedulers admit optimistically and only discover a missed deadline after the request has already run.

Zero unsafe (deadline-missing) admissions across every one of those 300 thread-scaling runs and all 13 baseline-comparison configurations, where a comparable aggressive-transfer baseline let through up to 40% unsafe admissions under tight deadlines.

Under review, SN Computer Science

PRISM-CVM

Security

Confidential virtual machines on AMD SEV-SNP and Intel TDX hide guest memory from the host, which removes the view that hypervisor-level malware detectors rely on. The open question is whether the disk-request metadata the host must still serve (address, size, direction, time) is enough to detect ransomware.

AUROC 0.981 on the same hardware and 0.966 on hardware never seen in training: level with intrusive memory-based features, and better on the unseen machine.

All research

Products

Original research, packaged into things you can deploy.

Every product below solves a specific, named problem, and we can tell you exactly how much better the result is.

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AI infrastructure

SHARD Gateway

A reverse proxy that sits in front of vLLM and makes a real admission decision before a request reaches the GPU.

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AI infrastructure

SHARD Context

Shrinks what you send to an LLM without losing the facts that have to be exactly right.

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AI infrastructure

SHARD CodeContext

Compiles the smallest slice of your repository a coding task actually needs, under a hard token budget.

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Have a hard systems problem that needs solving?

Whether it's a triage pipeline, an ERP rollout, or a performance ceiling you can't engineer around, tell us what you're building and we'll tell you honestly whether we're a fit.

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