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HOPFIELD LABS

Software & AI studio engineering modern web platforms, native mobile applications, and production-grade GenAI integrations for startups, SMEs, and academic capstone researchers.

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Projects Built to Solve Real Problems

Take a closer look at our projects, the challenges behind them, and the solutions we built. Explore our work across web development, mobile applications, and AI.

HEALTHTECH STARTUP · SERIES A-68% TRIAGE QUERY LATENCY

Aura Health Clinical Intelligence

GenAI & Healthcare

The Challenge

Unstructured electronic health records (EHR) caused 45-minute physician delays during triage, risking patient outcomes in emergency rooms.

Our Approach

Architected a HIPAA-compliant hybrid RAG pipeline using Claude 3.5, pgvector with dense+sparse re-ranking, and a low-latency Next.js 15 clinical dashboard.

Results

Sub-800ms RetrievalZero PHI Leakage SLA99.4% Extraction Accuracy

Technologies

Next.js 15FastAPIpgvectorClaude 3.5Docker
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ENTERPRISE LOGISTICS · 1,200 VEHICLES99.98% TELEMETRY ACCURACY

OmniTrack Mobile Fleet Telemetry

Mobile & Real-Time IoT

The Challenge

Legacy mobile dispatch platform dropped 12% of offline mobile telemetry packets in cellular blind zones across interstate delivery routes.

Our Approach

Engineered an offline-first React Native architecture with background SQLite sync, native Swift/Kotlin geo-fencing daemon, and TimescaleDB ingestion pipeline.

Results

Zero Packet Drop40% Lower Battery Drain1,200 Active Devices

Technologies

React NativeSwiftKotlinTimescaleDBNode.js
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ACADEMIC CAPSTONE94.6% F1 SCORE (GRADE A+)

NeuroScan EEG Automated Classifier

Deep Learning & FYP

The Challenge

Manual artifact detection in multi-channel EEG signals required 14 hours per patient dataset during epilepsy diagnostics clinical trials.

Our Approach

Trained a custom 1D-CNN transformer architecture in PyTorch with spectral wave decomposition, paired with a Next.js visualization interface for researchers.

Results

14h to 12s Analysis100% Defense ScoreIEEE Paper Acceptance

Technologies

PyTorchPythonNext.jsTailwind CSSFastAPI
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OPEN SOURCE RESEARCH TOOLING3.2x FASTER EVALUATION

SynthVector RAG Benchmarking Suite

Developer Tooling

The Challenge

Engineering teams lacked automated test suites to measure retrieval hallucination rates across diverse vector embedding models.

Our Approach

Created an open-source synthetic dataset generator and precision benchmark CLI comparing OpenAI, Cohere, and local sentence-transformers.

Results

450+ GitHub StarsAutomated CI TestingZero Hallucination Regressions

Technologies

TypeScriptPythonCLIVitestpgvector
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