Turn Idle GPUs Into Revenue

ParallelIQ is the model-aware control plane for GPUaaS — enforcing policy, visibility, and predictable economics across tenants, models, and clusters

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Why AI Infra Is Breaking?

AI infrastructure today wasn’t designed for the way modern models behave.

ParallelIQ addresses the three structural failures at the core of AI operations

Zero Visibility Into AI Workloads

Most teams don’t know which models are running, which versions are deployed, or how pipelines depend on each other.

Impact: Unknown risk, unpredictable cost, and operational blind spots.

Impact: unknown risk, unpredictable cost, and operational blind spots.

Our solution: Delivers a complete model inventory, dependency mapping, and clear workload insights.

PIQC Benefit: full model inventory, dependency mapping, and workload insights.

GPUs Are Busy — But Not Productive

Inefficient batching, incorrect concurrency, poor autoscaling, and suboptimal instance selection keep GPUs active without delivering proportional throughput.

Impact: GPU bill grows faster than throughput.

Our solution: Provides model-aware profiling, efficiency signals, and clear guidance to eliminate waste.

PIQC Benefit: profiling, efficiency warnings, and model-aware optimization.

No Clarity on What's Actually Running

Schedulers, autoscaling, and observability were designed for stateless web traffic — not memory- heavy ML inference pipelines with strict latency requirements.

Impact: Unstable scaling, unpredictable latency, and operational chaos.

Impact: poor scaling, unpredictable latency, and operational chaos.

Our solution: Provides Al-aware runtime signals, compliance checks, and dependency-driven orchestration readiness.

PIQC Benefit: AI-aware insights, compliance checks, and dependency-driven orchestration readiness.

Meet ParallelIQ
The AI-Runtime Intelligence Layer

Meet ParallelIQ The AI-Runtime Intelligence Layer

ParallelIQ gives ML and platform teams the visibility, context, and intelligence needed to run AI workloads efficiently at scale.

Model & Workload Discovery

Automatically identify every model, GPU, batch size, and runtime configuration across your cluster.

Real GPU Cost & Efficiency Mapping

Link throughput, memory behavior, and scaling patterns directly to GPU spend and efficiency.

Predictive Orchestration

Move beyond reactive autoscaling with orchestration that anticipates GPU demand before spikes occur.

Declarative Model Metadata (ModelSpec)

Give infrastructure a machine-readable description of model attributes, dependencies, and operational requirements.

Talk to an Expert

Expert Services to Optimize Your AI Infrastructure

ParallelIQ pairs deep AI-runtime expertise with hands-on execution to help teams reduce waste, improve reliability, and scale with confidence.

1–2 weeks

Infrastructure Audit

A comprehensive assessment of your GPU fleet, AI workloads, spend, and deployment architecture.

GPU utilization and efficiency report

Cost allocation and spend attribution

Latency and throughput profiling

Compliance and best-practice gaps

Get Audit Overview (PDF)

2–4 weeks

Optimization Sprint

Hands-on engineering to eliminate inefficiencies and harden your AI infrastructure.

Ongoing

Managed Optimization

Continuous oversight as models, workloads, and costs evolve.

1–2 weeks

Infrastructure Audit

A comprehensive assessment of your GPU fleet, AI workloads, spend, and deployment architecture.

GPU utilization and efficiency report

Cost allocation and spend attribution

Latency and throughput profiling

Compliance and best-practice gaps

Get Audit Overview (PDF)

2–4 weeks

Optimization Sprint

Hands-on engineering to eliminate inefficiencies and harden your AI infrastructure.

Ongoing

Managed Optimization

Continuous oversight as models, workloads, and costs evolve.

Products

Core building blocks that bring visibility, control, and efficiency to AI infrastructure.

Open-Core

PIQC Introspect

Your cluster’s X-ray.

Complete model inventory

GPU and accelerator characteristics

AI workload detection

Static and runtime configuration insights

Launch Introspect (Free)

Private Beta

Predictive Orchestration

Orchestration built for ML — not microservices.

Predicts GPU demand ahead of spikes

Reduces cold-start and warm-up latency

Manages hot, warm, and cold GPU pools

Plans capacity with cost awareness

Join Private Beta

Open Schema

ModelSpec

A machine-readable contract for running models in production.

Model dependencies and pipeline context

GPU, memory, and runtime requirements

Latency and throughput SLOs

Security, compliance, and guardrails

View on Github (Coming soon)

Partners & Ecosystem

Call out the partner types

GPU Cloud Providers

Scalable, high-performance GPU infrastructure for AI training and inference, available globally across cloud and on-prem environments.

Role: compute capacity, elasticity, hardware innovation

Role: trust, auditability, and risk management

AI monitoring, security, and compliance vendors for regulated production.

Role: trust, auditability, and risk management

ML Platforms

End-to-end ML platforms for streamlined development, deployment, and management at enterprise scale.

Role: developer productivity and ML workflows

Universities & HPC Centers

Leading research institutions advancing AI systems, algorithms, and high-performance computing through cutting-edge research.

Role: innovation, validation, and next-generation architectures

GPU Cloud Providers

Scalable, high-performance GPU infrastructure for AI training and inference, available globally across cloud and on-prem environments.

Role: compute capacity, elasticity, hardware innovation

Role: trust, auditability, and risk management

AI monitoring, security, and compliance vendors for regulated production.

Role: trust, auditability, and risk management

ML Platforms

End-to-end ML platforms for streamlined development, deployment, and management at enterprise scale.

Role: developer productivity and ML workflows

Universities & HPC Centers

Leading research institutions advancing AI systems, algorithms, and high-performance computing through cutting-edge research.

Role: innovation, validation, and next-generation architectures

GPU Cloud Providers

Scalable, high-performance GPU infrastructure for AI training and inference, available globally across cloud and on-prem environments.

Role: compute capacity, elasticity, hardware innovation

Role: trust, auditability, and risk management

AI monitoring, security, and compliance vendors for regulated production.

Role: trust, auditability, and risk management

ML Platforms

End-to-end ML platforms for streamlined development, deployment, and management at enterprise scale.

Role: developer productivity and ML workflows

Universities & HPC Centers

Leading research institutions advancing AI systems, algorithms, and high-performance computing through cutting-edge research.

Role: innovation, validation, and next-generation architectures

Case Studies

Real results: lower costs, faster launches, longer runway.

Training

Cutting AI Training Costs by 40% — No Trade-Offs in Performance

a computer chip with the letter a on top of it

Training

Faster AI Model Releases with 40% Fewer Incidents

Training

Cutting Drift Detection by 85%: Observability that Transforms MLOps

Training

Compliance-Aware AI Data Infrastructure for Healthcare

The AI Infrastructure Journal

Deep dives into architecture, performance tuning, and operational excellence.

AI/ML Model Operations

What Matters to a GPUaaS Tenant

AI/ML Model Operations

Beyond Prompt → Code: The Real Systems Challenges Behind Coding Foundation Models

AI/ML Model Operations

What Matters to a GPUaaS Provider

AI/ML Model Operations

What Matters to a GPUaaS Tenant

AI/ML Model Operations

Beyond Prompt → Code: The Real Systems Challenges Behind Coding Foundation Models

AI/ML Model Operations

What Matters to a GPUaaS Provider

AI/ML Model Operations

The #1 Silent Killer of GPUaaS Businesses

View All Blogs

Don’t let performance bottlenecks slow you down. Optimize your stack and accelerate your AI outcomes.

Start for Free

Don’t let performance bottlenecks slow you down. Optimize your stack and accelerate your AI outcomes.

Start for Free

Don’t let performance bottlenecks slow you down. Optimize your stack and accelerate your AI outcomes.

Start for Free

Don’t let performance bottlenecks slow you down. Optimize your stack and accelerate your AI outcomes.

Start for Free

Meeting your AI infrastructure needs with scalable, secure, and seamless services.

Products

Introspect

Predictive Orchestration

ModelSpec

Services

Infrastructure Audit

Optimization Sprint

Managed Optimization

Company

Blog

Case Studies

About

Terms & Conditions

Meeting your AI infrastructure needs with scalable, secure, and seamless services.

Products

Introspect

Predictive Orchestration

ModelSpec

Services

Infrastructure Audit

Optimization Sprint

Managed Optimization

Company

Blog

Case Studies

About

Terms & Conditions

Meeting your AI infrastructure needs with scalable, secure, and seamless services.

Products

Introspect

Predictive Orchestration

ModelSpec

Services

Infrastructure Audit

Optimization Sprint

Managed Optimization

Company

Blog

Case Studies

About

Terms & Conditions

Control Plane Dashboard Gallery

Provider View

Tenant View

Why AI Infra Is Breaking?

ParallelIQ addresses the three structural failures at the core of AI operations

Zero Visibility Into AI Workloads

GPUs Are Busy — But Not Productive

No Clarity on What's Actually Running

Meet ParallelIQThe AI-Runtime Intelligence Layer

Meet ParallelIQ The AI-Runtime Intelligence Layer

Model & Workload Discovery

Real GPU Cost & Efficiency Mapping

Predictive Orchestration

Declarative Model Metadata (ModelSpec)

Expert Services to Optimize Your AI Infrastructure

Infrastructure Audit

Optimization Sprint

Managed Optimization

Infrastructure Audit

Optimization Sprint

Managed Optimization

Products

PIQC Introspect

Predictive Orchestration

ModelSpec

Partners & Ecosystem

Partners & Ecosystem

Case Studies

Cutting AI Training Costs by 40% — No Trade-Offs in Performance

Faster AI Model Releases with 40% Fewer Incidents

Cutting Drift Detection by 85%: Observability that Transforms MLOps

Compliance-Aware AI Data Infrastructure for Healthcare

Cutting AI Training Costs by 40% — No Trade-Offs in Performance

Faster AI Model Releases with 40% Fewer Incidents

Cutting Drift Detection by 85%: Observability that Transforms MLOps

Compliance-Aware AI Data Infrastructure for Healthcare

Cutting AI Training Costs by 40% — No Trade-Offs in Performance

Faster AI Model Releases with 40% Fewer Incidents

Cutting Drift Detection by 85%: Observability that Transforms MLOps

Compliance-Aware AI Data Infrastructure for Healthcare

The AI Infrastructure Journal

Don’t let performance bottlenecks slow you down. Optimize your stack and accelerate your AI outcomes.

Don’t let performance bottlenecks slow you down. Optimize your stack and accelerate your AI outcomes.

Don’t let performance bottlenecks slow you down. Optimize your stack and accelerate your AI outcomes.

Meet ParallelIQ
The AI-Runtime Intelligence Layer