Proven Engineering

Bespoke AI Case Studies

We do not just construct simple mockups. We deploy high-performance, high-compliance machine learning systems that save actual enterprise capital.

Finance & Compliance

Secure Enterprise RAG Engine

Client: Metro Financial Group

91% Faster Document Search

The Friction

Metro Financial Group had over 100,000 regulatory guidelines, compliance files, and investment logs spread across disjointed servers. Underwriters spent up to 6 hours daily searching records, introducing massive human error risks and deal delays.

Engineered Solution

We engineered a VPC-isolated RAG search assistant. The system parses PDF, Docx, and SQL files, structures them using LlamaIndex hierarchical chunking, and indexes them in a secure Qdrant vector store. Sub-second semantic search is paired with strict role-based access controls.

System Architecture

Ingestion pipeline parses documents with LlamaParse -> Chunks vectors with text-embedding-3-large -> Stores in Qdrant VPC instance -> Llama-3.1-70B running on private Azure GPU node generates responses with verified citations.

Quantifiable Outcomes

  • Document search time sliced from 6 hours to less than 30 seconds.
  • 100% private deployment: no regulatory PHI/PII data escaped their secure subnet.
  • Zero compliance underwriting omissions reported since active deployment.
Integrated Technologies:
Llama-3.1QdrantLlamaIndexAzure GPUDocker
Manufacturing & Robotics

Edge Computer Vision QC Scanner

Client: Sato Heavy Industries

Defect Escape Rate < 0.05%

The Friction

Sato Heavy Industries manufactured high-speed turbine shafts. Manual inspections on conveyor belts failed to detect microscopic hairline fractures, resulting in occasional catastrophic rotor turbine failures post-assembly.

Engineered Solution

We deployed custom high-speed computer vision systems scanning conveyor shafts in real time. Deployed on NVIDIA Jetson Edge devices, the YOLOv8 model classifies microscopic surface defects at 60 frames per second, instantly triggering pneumatic defect ejectors.

System Architecture

High-FPS camera capture -> TensorRT optimized YOLOv8 segmentation on NVIDIA Jetson edge nodes -> Local MQTT broker alerts factory PLC -> Pneumatic ejector clears defective SKUs.

Quantifiable Outcomes

  • Microscopic defect escapes plummeted from 2.4% to less than 0.05%.
  • Conveyor-belt visual inspections operate 24/7/365 with zero inspection fatigue.
  • Prevented millions of dollars in potential product warranty liability.
Integrated Technologies:
YOLOv8TensorRTNVIDIA JetsonPyTorchMQTT
FinTech & Payment Gateway

Predictive Analytics & Fraud Shield

Client: GlobalPay Commerce

Reclaimed $4.2M in Fraud

The Friction

GlobalPay Commerce processed millions of payment transactions daily. Dynamic fraud vectors bypassed traditional rule-based filters, costing the platform massive payment chargeback penalties and lost merchant credibility.

Engineered Solution

We engineered a machine learning payment profiling pipeline. An XGBoost model trained on historical fraud logs evaluates incoming payment metadata (device, geolocation, velocity, volume) in less than 5 milliseconds, flagging suspicious profiles for instant verification.

System Architecture

Incoming payment request API -> Feature extraction -> XGBoost inference on AWS SageMaker -> Sub-5ms scoring -> Redis state management -> Fraud alert trigger.

Quantifiable Outcomes

  • Successfully blocked $4.2 million in fraudulent payment attempts within 6 months.
  • Inference completes in 4.8ms, introducing zero perceived transaction latency.
  • Slashed merchant dispute chargeback penalties by 68%.
Integrated Technologies:
XGBoostAWS SageMakerFastAPIRedisScikit-Learn
Healthcare & Patient Care

Ambient Clinical Intake Assistant

Client: CareAll Healthcare System

2.1 Hours Saved Daily per Dev/Doc

The Friction

Physicians at CareAll spent up to 3 hours daily typing up clinical intake files. This severe documentation burnout drastically lowered daily patient consultation times and degraded clinical diagnostic quality.

Engineered Solution

We created a HIPAA-compliant voice ingestion system. The tablet recorder captures the patient-physician discussion ambiently, Whisper translates the conversation, and a fine-tuned Med-PaLM model structures the medical transcript directly into standard EHR note layouts.

System Architecture

Ambient tablet microphone -> High-speed Whisper audio-to-text -> Med-PaLM custom instruction fine-tuned pipeline -> Strict PII redact validator -> Direct FHIR EHR API update.

Quantifiable Outcomes

  • Doctors save an average of 2.1 hours daily on manual clinical documentation.
  • Increased daily patient consultation capacity by 34% per clinic.
  • 100% HIPAA and GDPR audit compliance using private local cloud servers.
Integrated Technologies:
Whisper-LargeMed-PaLMNext.jsPythonFHIR APIs
Secure Prototyping

Let's Design Your Secure Proof-of-Concept

Unsure of LLM hallucinations or vector storage setups? We build secure, sandbox environments loaded with your private data to illustrate functionality before committing to heavy scaling costs.

Consult a Solutions Architect