A amit-brahmbhatt.dev

Portfolio — AI systems · Security · Quantum

Hi, I'm Amit Brahmbhatt.

Software engineering leader & technical founder

I build AI systems, cybersecurity tooling, and high-performance computing infrastructure. My work falls into three areas below — six projects are the core of it, and the full repository catalog has the rest.

01 — AI & GPU

AI & GPU Systems

Making accelerated computing actually faster — CUDA performance engineering, GPU workload infrastructure, and the economics of LLM inference.

gada-gpu-analytics

ProblemKernel benchmarks report GPU wins that vanish the moment you measure the whole application, because nobody accounts for PCIe data movement.

EvidenceThe optimized CUDA kernel runs 24.2× faster than a 24-thread AVX2 CPU baseline at 1672 GB/s (93.3% of RTX 5090 DRAM bandwidth), yet the complete GPU application stays ~1.4× slower because the host-to-device transfer dwarfs the kernel.

cachelens

ProblemLLM prompt caches are prefix-sensitive, so tiny changes such as timestamps, UUIDs, reordered tools, or volatile context can invalidate thousands of reusable tokens.

EvidenceOn a measured browser-use workload, CacheLens reduced modeled input cost from $0.8678 to $0.5289 — 39.1% recovered, with measured recoverable savings ranging from 23–51% across tested session shapes.
02 — Trustworthy AI

Trustworthy / Secure AI

Evidence over vibes — authorization with provenance, adjudication that tries to falsify itself, and reliability layers for agent systems.

proofgate-pq

ProblemAn agent's signature proves who asked for an action, not that the exact action was independently checked, unchanged since approval, or never executed before.

EvidenceOn an RTX 5090, the full protected 24-qubit workflow measured 5.18× faster than the fixed 8-thread CPU reference, backed by 212 tests and a red-team pass that confirmed no exploitable authorization bypass.

decisiongate

ProblemMultiple LLMs can agree on a convincing conclusion while sharing the same unsupported assumption, and agreement is not independent evidence.

EvidenceEvery claim is tagged EXPLICIT, INFERENCE, ASSUMPTION, CONTRADICTED, or UNKNOWN, and the engine resolves to a deterministic GO, NO_GO, or HUMAN_VERIFY with report confidence forced to zero by any unresolved critical predicate.
03 — Quantum

Quantum & Scientific Computing

Quantum protocols, error correction, and benchmarks run against real hardware — including honest null results.

entangl

ProblemAgents are already buying ads, booking travel, and moving money on behalf of humans over messages protected by cryptography that a quantum computer will break, while harvest-now-decrypt-later adversaries record everything today.

EvidenceA live four-message buyer/seller negotiation completes in 1.40 s with every message encrypted under ML-KEM-1024 (FIPS 203) and signed with ML-DSA-87 (FIPS 204), the relay reading zero payload bytes, rogue agents blocked, and tampered messages rejected.

q-tensor

ProblemTensor-network claims for noisy quantum simulation conflate unique-record harvesting with real execution speedup, and nobody had measured exactly where batching actually wins.

EvidenceOn the exact public 50-qubit/200-gate Figure-3 workload, tensor-network proportional sampling measured a 6.875× speedup over CUDA-Q TensorNet at equal shots, and a preregistered IBM Kingston study showed the frozen calibration-informed model beating the ideal noiseless model at all four tested depths.

About

Software engineering leader and technical founder working across AI systems, security, and HPC — from CUDA kernels on an RTX 5090 to post-quantum protocols. Based in Milpitas, California.

Building in AI infrastructure, security, or quantum?

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