Projects

In-depth case studies covering system design, technical decisions, reliability engineering, and real-world impact. Hover any card to preview the architecture.

Architecture preview

Visual PipelineUser-defined nodesOrchestration APIFastAPI + GraphQLWorker PoolCelery + RedisResultWebhook / APIEnterprise isolation via Kubernetes namespaces + AWS VPC

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Salt AI
60% faster integrationsJan 2025 – Mar 2026

AI Workflow Orchestration Platform

Distributed execution system and orchestration layer for AI workflows — converting visual pipelines into production-ready APIs with reliable retry, dependency scheduling, and enterprise connector integrations.

PythonFastAPICeleryRedisKubernetes+3
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Architecture preview

Epic / CernerFHIR + HL7 v2EHR GatewayNormalize + RouteNLP CodingICD-10 / CPTChart AILLM summariesEHR WriteAudit loggedKafka event bus decouples EHR ingestion from AI services · HIPAA-compliant throughout

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Ambience Health
Reduced physician admin timeAug 2021 – Dec 2024

Healthcare AI & EHR Integration Platform

Clinical AI platform integrating with Epic and Cerner via FHIR/HL7, automating medical coding with NLP models, and reducing physician administrative burden through intelligent chart summarization and workflow automation.

PythonFastAPINode.jsKafkaFHIR+5
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Architecture preview

Member PortalReact · Node.jsCare CoordinationNurse workflowsPop HealthPython · Risk scoringPostgreSQLSource of truthMedicare Advantage platform · Domain-separated services · Query-optimized PostgreSQL

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Zing Health
Medicare Advantage platformMay 2018 – Aug 2021

Medicare Advantage Healthcare Platform

Full-stack healthcare platform serving Medicare Advantage members — spanning a self-service Member Portal, a Care Coordination system for nurses and case managers, and a Population Health analytics platform for proactive care interventions.

ReactNode.jsPostgreSQLPythonREST APIs+2
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Architecture preview

Training DataGCS / ColossusTF TrainingGPU / TPU clusterModel RegistryVersioned + evalServingCanary rolloutpasses evalpromoteCheckpoint-based fault tolerance · Canary deployment with automatic quality-based rollback

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Google
Google-scale ML infraFeb 2015 – Aug 2021

ML Infrastructure & Training Pipelines

Production ML infrastructure for training and deploying speech recognition, computer vision, and recommendation models at scale — building the systems that let research teams productionize experimental models safely.

TensorFlowPythonDistributed SystemsGPU ClustersML Pipelines+1
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Each case study follows a consistent structure: Problem → Solution → Architecture → Technical Decisions → Reliability → Impact.