Strengthening an AI-powered data platform used by hundreds of Fortune 500 firms

Production-ready AI microservices, API hardening, and performance benchmarking

Our work on the client’s platform centered on AI workloads, GPU utilization, platform performance, and production readiness. Within this scope, our experts evaluated the infrastructure and network protocols for AI inference, prototyped a computer vision tool, hardened the platform API, and maximized its QA coverage.

Key deliverables

• Automated unit and end-to-end test suites covering positive, negative, edge-case, authentication, payload, and service-error scenarios
• API hardening through stronger input validation, error handling, timeout enforcement, and improved failure handling
• Containerized proof of concept for transforming multiple image formats and scene descriptions into standardized RGB images, with Vision-Language Model and vector database integration
• HTTP vs. gRPC performance benchmarking and prompt optimizations for NVIDIA inference models and NVIDIA NIM workloads
• Evaluation of a Rancher-based infrastructure, including Red Hat Enterprise Linux and NVIDIA plugins, validating its capability to run AI workloads
• Multi-format datasets collected and stored in the client’s internal environment for testing and validation

Technologies

Golang, Kubernetes, Prometheus, Grafana, MongoDB, RAG, Vector Databases, Milvus, Rancher