Research & Innovations

The mechanism is ours. The result is yours to see.

Every research program here is patent-backed. What's public is the problem it solves and exactly how much better the measured outcome is.

Original research — patent-backed

H-PLHF-Core

High-performance data infrastructure

high-performance infrastructureresource-bounded systemsdata structures

The problem

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.

Validated across 1,414 real benchmark runs on production-grade cloud hardware — no simulated results.

How much it solves it

Concurrent throughput scales from 54.8k to 1.83M operations per second across 1–64 threads, overtaking common alternative approaches once real contention kicks in.

Adds no measurable overhead on 11 of 13 tested workload patterns.

Builds a queryable snapshot 5.7×–12.5× faster than alternative approaches, with a disclosed trade-off on a different metric depending on deployment pattern.

Original research — patent-backed

SHARP-WCE

Medical imaging

medical imagingresource-bounded systemsselective prediction

The problem

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.

Evaluated on 47,161 labelled frames across 43 real patient studies, against six alternative approaches.

How much it solves it

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.

Full data-durability guarantees cost 45.8%–48.4% latency overhead, reduced substantially once batched.

A common alternative approach shows a 200×–500× tail-latency spike at the 99.9th percentile that is completely invisible if you only check the average.

Active R&D — not yet published

SHARP-Flow

Network security

network securityresource-bounded systems

The problem

Detecting and mitigating intrusions at line rate needs the same fast-lookup, priority-ranking, and resource-budgeting problem our infrastructure research already solves elsewhere — applied to live network traffic instead of stored data.

Core validation work is complete; traffic-scale benchmarking has not started.