Technology Partners

Collaboration is the Cornerstone of Excellence

At ExamRoom.AI, we believe that strong partnerships are essential to driving innovation and raising the bar for what’s possible in exam integrity and assessments. We are proud to work with industry leaders like Intel, our Platinum partner, along with NVIDIA, Vonage, and Amazon Web Services (AWS), to deliver advanced, reliable, and accessible testing solutions.

These collaborations, along with our relationships with top educational institutions, certification bodies, and global organizations, are built on trust, shared values, and a commitment to empowering learners everywhere. Together, we bring powerful technologies and deep expertise to create secure, seamless, and inclusive exam experiences.

Through these partnerships, we’re not just supporting today’s testing needs, we’re helping shape the future of assessment and making a real difference in how people learn, certify, and grow.

AWS

Our Technology Partnership with AWS

Powering Scalable, Intelligent Solutions in the Cloud

We are proud to be an AWS Technology Partner, combining our innovation with the reliability and scale of Amazon Web Services. This strategic partnership enables us to deliver cutting-edge cloud and AI solutions that help businesses move faster, operate smarter, and grow confidently.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and widely adopted cloud platform, offering over 200 fully featured services from data centers globally. Our partnership unlocks access to:

Cloud Infrastructure: Highly scalable, secure, and globally available computing environments.
AI/ML Services: Tools like Amazon SageMaker, Bedrock, Rekognition, and Comprehend to build and deploy machine learning models at scale.
Data & Analytics: Real-time processing, data lakes, and predictive analytics with services like Redshift, RDS, and Kinesis.
Security & Compliance: Built-in controls for GDPR, HIPAA, ISO 27001, and more—backed by AWS’s best-in-class cloud security.

What We Deliver with AWS

Feature	How It Helps
Smart Automation	AI-powered workflows and recommendations using AWS AI & ML tools
Faster Deployments	CI/CD pipelines with AWS CodePipeline and ECS/Fargate support
Real-Time Insights	Integrated data streams and dashboards powered by AWS analytics
Enterprise-Grade Security	Multi-layer protection, IAM roles, and VPC isolation for every customer

Use Cases Powered by AWS

Intelligent Document Processing using Amazon Textract + Comprehend
AI-Driven Recommendations via Amazon Personalize
Serverless Web Apps running on AWS Lambda + API Gateway
Custom ML Models built and deployed with Amazon SageMaker

Our Joint Commitment

This partnership means more than infrastructure—it’s a shared commitment to innovation, agility, and delivering value to our customers. With AWS, we’re not just building in the cloud; we’re building for the future.

Intel

Our Technology Partnership with Intel

Accelerating AI with Cutting-Edge Hardware & Model Optimization

We are proud to partner with Intel®, a global leader in semiconductor innovation, to deliver high-performance, AI-optimized solutions. By integrating the latest Intel platforms and toolkits, we’re pushing the boundaries of what’s possible in edge and cloud AI.

What This Platinum Partnership Brings

Next-Gen Intel Hardware

We leverage Intel’s most advanced processors and platforms to maximize performance and efficiency:

Intel® Xeon® 8480+ for enterprise-grade compute scalability
Intel® Arrow Lake & Meteor Lake for power-efficient edge AI and hybrid workloads
Intel® Gaudi® and GNR (Granite Rapids) architectures for large-scale model training and inference

Optimized AI with OpenVINO™

Our solutions are fine-tuned using Intel’s OpenVINO™ toolkit, unlocking:

Model compression without loss of accuracy
Faster inference across CPUs, GPUs, NPUs, and FPGAs
Seamless edge-to-cloud AI deployment
Lower latency, higher throughput, and energy-efficient processing

Co-Developed Solution Architecture

Through close collaboration with Intel’s solution architects, we co-design intelligent pipelines that:

Improve AI model accuracy through hardware-aware optimization
Maximize resource efficiency across Intel platforms
Enable cross-device interoperability for real-world production AI

"Our joint solution architecture allows us to not only boost performance but deliver measurable improvements in real-world AI deployment scenarios."

Co-Branded Thought Leadership & Marketing

We’ve also partnered with Intel to share insights, use cases, and AI success stories across global platforms:

Podcast Appearances on AI innovation and optimization
YouTube videos & demos showcasing real-world benchmarks
LinkedIn Articles and posts highlighting solution architectures
Joint Webinars and technical deep dives
Co-branded Campaigns on platforms like Spotify

Recent Highlights

Joint optimization of large vision model on Arrow Lake using OpenVINO
Performance benchmarking of hybrid workloads on Arrow Lake
Podcast feature on "Scalable AI in Production" — Listen on Spotify
Featured on Intel’s Developer Zone & LinkedIn Tech Pulse

Microsoft Azure and OpenAI

Our Strategic Partnership with Microsoft Azure & OpenAI

Enterprise-Grade Embeddings and AI, Built for Deployment at Scale

We’ve partnered with Microsoft Azure and OpenAI to deliver advanced Enterprise Embedding models and AI capabilities that are secure, scalable, and production-ready. This collaboration allows us to build and deploy solutions that understand context, retrieve relevant knowledge, and generate meaningful interactions — all while meeting the highest standards of enterprise compliance.

What Are Enterprise Embeddings?

Embeddings are dense vector representations of text that enable deep semantic understanding for tasks like:

Semantic search
Document classification
Personalization & recommendations
Context-aware chat and retrieval-augmented generation (RAG)

With Azure OpenAI’s embedding models, we build high-performance, cost-effective AI pipelines that understand language the way humans do — across millions of documents or records.

Built on Azure, Powered by OpenAI

Our solutions leverage:

OpenAI’s Embedding Models (e.g., text-embedding-3-large) for best-in-class vector quality
Azure Cognitive Search and Vector DB integrations for low-latency retrieval
Azure OpenAI Service for secure, compliant deployment within enterprise clouds
Scalable Inference Infrastructure using Azure Kubernetes Service (AKS) or Azure ML

Enterprise Benefits

Feature	Benefit
Private, Region-Based Deployment	Ensures data residency and compliance
Enterprise-Ready SLAs	Backed by Microsoft’s global cloud platform
Multi-Modal Extension	Combine text, image, and code understanding
Seamless API Integration	Easy to embed in internal tools or public-facing apps

Sample Use Cases

Enterprise Knowledge Retrieval from SharePoint, Confluence, and internal docs
Semantic Search across large PDFs, emails, and policy repositories
Context-Aware Chatbots for customer support or employee self-service
Document Summarization & Entity Extraction at scale

OpenAI + Azure in Action

Through this partnership, we deliver AI solutions that are:

Accurate — built on high-quality embedding models
Scalable — hosted on enterprise Azure infrastructure
Secure — compliant with SOC 2, GDPR, HIPAA, and more

Joint Highlights

Early access partner to OpenAI’s newest embedding models
Co-branded case study with Azure AI on RAG deployment
Featured webinar: "Scaling Semantic Search with Azure OpenAI"
API integrations and performance benchmarks published on GitHub

Nvidia

Our Technology Partnership with NVIDIA

Accelerated AI, Seamlessly Deployed on GPU-Optimized Hardware and Containers

We partner with NVIDIA to bring you high-performance AI solutions built on world-class GPU hardware, CUDA-accelerated frameworks, and production-ready Docker environments. This end-to-end collaboration enables us to train, optimize, and deploy deep learning models at scale — reliably and efficiently.

Hardware Support Across the Stack

Our AI infrastructure is powered by NVIDIA’s cutting-edge GPU lineup, ensuring optimal performance for every stage of the AI lifecycle:

Hardware	Use Case
NVIDIA H100 / A100	Large model training & high-throughput inference in the cloud or datacenter
NVIDIA L40 / L4 / RTX 5000 Ada	Workstation-grade performance for development, fine-tuning, and prototyping
NVIDIA Jetson Orin / Xavier / Nano	Edge AI deployment with real-time performance and low power footprint
NVIDIA DGX Systems	Scalable, out-of-the-box deep learning systems for enterprises
NVIDIA GPU Cloud Instances	Support for AWS (p4d, g5), Azure ND/H100, GCP A2 instances

Dockerized AI Pipelines

Our AI stack integrates with NVIDIA NGC Docker containers, ensuring:

One-command deployment with preloaded CUDA, cuDNN, and framework libraries
Version consistency for reproducible experiments and production models
Support for Triton Inference Server with multi-model and multi-framework runtime
Auto-scale integration with Kubernetes + GPU node pools

Optimized Model Deployment

We optimize your trained models for maximum speed and efficiency using:

NVIDIA TensorRT for quantization and GPU-specific graph optimization
cuBLAS / cuDNN acceleration in TensorFlow & PyTorch
Multi-GPU scaling using NCCL and Horovod
Real-time telemetry with NVIDIA DCGM, Prometheus, and Grafana integration

TrueFoundry

Our Platform Enablement Partnership with TrueFoundry

Streamlined ML Deployment, Hardware Optimization & Observability at Scale

We partner with TrueFoundry to operationalize AI workloads with maximum efficiency — across multiple hardware environments and deployment targets. Their platform allows us to automate model deployment, optimize GPU utilization, and monitor model performance in real time, whether in the cloud, on-prem, or at the edge.

Key Capabilities with TrueFoundry

Capability	Benefit
Multi-Model Deployment	Deploy and manage hundreds of models with autoscaling and rollout strategies
Hardware Optimization	Efficient GPU/CPU resource allocation across training and inference workloads
Real-Time Monitoring	Track latency, throughput, errors, and drift from a single pane of glass
Cross-Cloud Compatibility	Works seamlessly with AWS, GCP, Azure, and on-prem clusters
CI/CD for ML Models	GitOps-driven deployments for reproducibility and control

Built for Private Clusters & Network-Safe Deployments

TrueFoundry supports zero-trust architectures and fine-grained network controls, ensuring all model endpoints and data services operate securely within isolated environments.

Security Layer	Capability
Private Kubernetes Clusters	Run entirely within customer-controlled VPCs or bare-metal servers
Service Mesh Integration	Enforce mutual TLS, access controls, and secure service-to-service communication
Firewall & Network Policy Enforcement	Define strict ingress/egress rules per workload
Private Endpoint Support	No public IP exposure; traffic flows only through secure internal routes
Role-Based Access Control (RBAC)	Secure platform access at user, model, and namespace level

Flow-Aware Network Layering

TrueFoundry provides a layered network architecture that segments internal ML traffic:

Control Plane: Internal API, CI/CD, and orchestration logic
Data Plane: Inference traffic, model outputs, and streaming logs
Monitoring Plane: Metrics pipelines to Prometheus/Grafana/Datadog
Air-Gapped Support: For highly secure environments with no external internet

Each layer is isolated using Kubernetes namespaces, network policies, and optionally service mesh policies like Istio or Linkerd.

Hardware Efficiency, Maximized

TrueFoundry helps us:

Run multiple models on shared GPU nodes to avoid underutilization
Automatically right-size infrastructure based on usage and model load
Isolate hardware-intensive jobs like fine-tuning or batch inference
Deploy latency-sensitive models in real-time pipelines with autoscaling

Whether using NVIDIA H100, Intel GNR, or Jetson Orin, we ensure each hardware target is fully optimized through TrueFoundry’s orchestration layer.

Full-Stack Observability

Track per-model and per-endpoint metrics (latency, CPU/GPU usage, memory)
Set alerts and anomaly detection for drift, failures, or scaling issues
View integrated dashboards or export metrics to Grafana, or Datadog

Collaboration Outcomes

Co-developed autoscaling strategy for multi-tenant GPU inference clusters
Integrated drift detection & logging into our RAG pipelines
Featured in upcoming joint blog post and LinkedIn campaign
TrueFoundry support embedded into our AI deployment workflow

Vonage/Tokbox

Real-Time Streaming Partnership with Vonage / TokBox

Peer-Peer, Server-Media, and Scalable WebRTC Infrastructure for Live AI, Video, and Collaboration

We’ve partnered with Vonage (formerly TokBox) to deliver low-latency, high-quality real-time streaming for AI-powered apps, collaborative tools, and media platforms. Whether you’re streaming from device-to-device or scaling up through media servers, our platform ensures end-to-end security, resilience, and observability.

Streaming Architecture: Peer-to-Peer and Media Relay Modes

Our system intelligently adapts between direct peer-to-peer (P2P) and media server–assisted (SFU/MCU) configurations:

Mode	Description	Use Case
P2P	- Ultra-low latency real-time communication - End-to-end encrypted direct connection	- 1:1 call, private communication - Adaptive bitrate optimization for consistent quality across varying network conditions - Support for up to 50 simultaneous peer connections in a single session
Peer-Media Server (SFU)	Each client sends a single stream; server relays to many	- Group calls, webinars, scalable video - Media-peer server relays for optimized traffic routing
Media-Peer Server (MCU)	Streams are mixed/composited at the server	Broadcasts, recording, unified layouts
Hybrid Adaptive	Dynamic switching based on bandwidth, geography, or device	Global or mobile-first platforms

Infrastructure Support & Deployment Flexibility

We deploy streaming infrastructure across multi-cloud and on-prem using Vonage APIs, integrated with our own deployment orchestration:

Elastic media server scaling across AWS, Azure, and private clouds
Edge caching and TURN/STUN server provisioning for NAT/firewall traversal
Geographically aware media routing for reduced latency and jitter
Private session routing and QoS metrics for regulated environments
24/7 technical monitoring and response team

Risk Management & Compliance

We implement a robust risk management layer for real-time communication:

Security	Control
E2E Encryption for P2P Streams	Full compliance with HIPAA/GDPR/CCPA
DTLS/SRTP + TLS 1.3	Secure transport over UDP/TCP
Session Risk Scoring	Detect and block anomalies, spam, or misuse
Audit Logging & Forensics	Full session trails, timestamped artifacts
DDoS & Media Flood Protection	Throttling, rate-limits, and CDN-level WAF policies

Monitoring, Alerting & Quality

Real-time stream analytics (FPS, bitrate, packet loss, jitter)
Self-healing fallback to TURN relays if peer connection fails
Integration with Grafana and Elastic APM
Optional session recording with secure cloud access (S3)

Partnership Advantages

Direct access to Vonage/TokBox's premium API tier and technical resources
Priority issue resolution and dedicated support channels
Early access to new features and capabilities
Custom solution design and optimization services
Competitive pricing structure through our volume partnership agreement