Technical Case Studies
Case Studies
Deep-dive technical breakdowns of real-world projects across 31 domains
Proven Results Across Projects
30-60%
Avg Cost Reduction
3-10x
Performance Improvement
8-12
Weeks to Deliver
100%
Client Satisfaction
All Case Studies
59 studiesExplore detailed technical breakdowns of real-world projects
Enterprise Auth
Okta SSO & SCIM Integration for Enterprise Health & Wellness Platform
An enterprise health and wellness SaaS platform needed to support large organizational customers who required Single Sign-On (SSO) for seamless employee access and automated user provisioning/deprovisioning via SCIM — a non-negotiable requirement for enterprise sales.
OktaSAML 2.0OIDCSCIM 2.0+7
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GPU Infrastructure
On-Off Scaling Pattern for AI & Video Processing Workloads
An AI-powered video processing platform needed to handle highly variable workloads — from zero jobs during off-hours to hundreds of concurrent video processing and AI inference tasks during peak times — without paying for idle GPU and compute resources.
Node.jsMongoDBRunPod APICloud VM APIs+6
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GPU Infrastructure
Leveraging RunPod for Scalable, Cost-Effective AI Inference
An AI-powered video analytics platform needed high-performance GPU compute for real-time object detection and inference across multiple concurrent video streams — without the prohibitive cost of dedicated GPU servers running 24/7.
RunPodDockerFastAPIPython+5
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Data Security
Contextual Encryption for LLM and Vector Database Pipelines
An enterprise AI platform needed to enable LLM-powered features (chat, search, document analysis) while ensuring sensitive data — PII, financial records, healthcare information — remained encrypted throughout the pipeline, including when stored as vector embeddings in a vector database.
AES-256-GCMAWS KMSMilvusPostgreSQL+6
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Vector Databases
Milvus Autoscaling on Kubernetes with EC2 and S3-Backed Persistent Storage
An AI platform with rapidly growing vector data (embeddings for search, recommendations, and RAG) needed their Milvus vector database to scale automatically based on query load and data volume — with durable, cost-effective storage that wouldn't be lost if pods restarted or nodes were replaced.
MilvusAmazon EKSKubernetes HPACluster Autoscaler+7
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Vendor Discovery
Intelligent B2B Supplier Search Engine with Elasticsearch
The vendor platform needed a high-performance search engine capable of handling complex multi-faceted queries across thousands of international suppliers with sub-second response times.
ElasticsearchNode.jsExpressTypeORM+4
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