Proven system outcomes
Engineered for production scale.
Real deployments from our 12-person specialized AI squad. Every study details the architectural bottleneck, custom model solution, and audited computational ROI.
Global Tier-1 Clearing Bank
$4.2M OPEX saved
Legacy fraud classification pipeline suffered 850ms latency spikes during high-volume market windows, forcing manual escalation on 14% of flagged transactions.
Engineered a low-latency vector retrieval scoring engine paired with quantized transformer models on custom Triton inference clusters with zero-downtime model updates.
Reduced inference latency to 18ms at peak load, eliminating manual escalation bottlenecks and preventing $18M in false-positive transaction halts.
Integrated Health Network
6.2x faster reviews
Clinical pathology review workflows were constrained by fragmented imaging formats and unindexed multi-gigabyte histological image scans.
Deployed a distributed vision-transformer pipeline with custom attention masking for multi-resolution patch processing and clinical decision support.
Cut pathology turnaround from 4 days to 45 minutes while achieving 99.4% concordance with peer-reviewed board benchmarks across 42,000 cases.
North American Freight Carrier
$9.1M annual margin
Static route scheduling engines failed to recalculate dynamic terminal bottlenecks, port delays, and weather anomalies in real time.
Developed reinforcement learning dispatch agents integrated with real-time telematics and predictive demand forecasts across 3,800 active tractor-trailers.
Lowered empty-mile rates by 22% and secured an audited $9.1M net operational margin improvement across four operating quarters.
Enterprise CRM Platform
12M daily queries
Traditional elastic keyword search failed contextual user intent across unstructured meeting notes and multi-tenant sales records.
Architected a hybrid sparse-dense vector search system using custom fine-tuned embeddings with sub-shard query routing and cache pre-warming.
Maintained sub-85ms p99 latency across 12M daily enterprise queries while lifting contextual retrieval accuracy by 64%.
Production AI systems that prove their value in weeks
See how engineering leaders deploy production models, reduce latency, and scale infrastructure without breaking existing workflows.
"CORTEX upgraded our legacy data infrastructure and delivered custom models that cut manual processing time immediately. The team worked alongside our engineers without disrupting daily pipelines."
Chief Data Officer, Acme Corp
"Their team built a dedicated MLOps pipeline on AWS that scaled our inference workloads fourfold while keeping compute expenses completely predictable. Measurable results within 60 days."
VP of Engineering, InnovateTech
"Deploying enterprise NLP models with strict compliance guardrails was our biggest bottleneck. CORTEX engineered a secure local retrieval system that hit production compliance on schedule."
Head of Infrastructure, Apex Logistics
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