Exafunction · 0 reviews

Exafunction

Accelerate deep learning inference while slashing infrastructure costs by up to 10x

Artificial Neural Network Software

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About Exafunction

Exafunction is a deep learning inference optimization platform designed to dramatically improve resource utilization and reduce operational costs for organizations running AI workloads at scale. The platform intelligently manages resource allocation and orchestration across distributed inference clusters, delivering up to 10x improvements in both performance and cost efficiency. By automating cluster management, load balancing, and resource scheduling, Exafunction eliminates infrastructure bottlenecks and enables teams to deploy models faster without manual tuning. The solution abstracts away complex infrastructure management, allowing data scientists and ML engineers to focus on model development and innovation. AiDOOS marketplace integration enables seamless deployment and governance of Exafunction across hybrid environments, while providing centralized monitoring, cost attribution, and optimization recommendations. The platform supports multiple deep learning frameworks and hardware configurations, making it adaptable to diverse enterprise infrastructures.

Challenges It Solves

Deep learning inference workloads consume excessive computational resources and incur high cloud infrastructure costs
Manual cluster management and resource allocation require specialized expertise and constant optimization effort
Inefficient GPU utilization and batch processing pipelines lead to underutilized hardware and wasted capital
Organizations lack visibility into inference performance metrics and cost attribution across deployed models
Complex multi-tenant environments require sophisticated scheduling to balance performance and resource constraints

10x

Improvement in resource utilization and cost efficiency

Average reduction in inference latency through optimized batching

Decrease in infrastructure costs for production AI workloads

Use Cases

High-Volume Real-Time Inference

Organizations running thousands of concurrent inference requests can leverage Exafunction's intelligent batching to maximize GPU utilization and reduce per-request latency while minimizing infrastructure costs.

64% Latency reduction with higher throughput per GPU

Multi-Model Production Deployment

Large enterprises with diverse deployed models benefit from centralized orchestration, automatic resource allocation, and per-model cost tracking across multiple inference pipelines.

48% Significant decrease in total infrastructure spending

Cost Optimization for Cloud AI

Organizations using cloud-based AI inference can dynamically scale resources and apply intelligent scheduling to reduce wasted compute cycles and minimize cloud billing.

75% Optimization of spot instance and reserved capacity utilization

Batch Processing Workloads

Data-intensive batch inference pipelines can be optimized through intelligent job scheduling and resource consolidation, enabling faster job completion with fewer resources.

56% Faster batch job completion times with reduced costs

Pricing

Pricing available on request

Exafunction pricing is customized based on your team size, integrations, and requirements. AiDOOS will get you a scoped proposal — for free.

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Key Features

Automated Cluster Orchestration

Intelligent resource scheduling and load balancing

Up to 10x improvement in resource utilization efficiency

Dynamic Batch Optimization

Automatic request batching for maximum throughput

64% reduction in inference latency per request

Cost Attribution & Monitoring

Real-time visibility into per-model inference costs

Enable chargeback and cost optimization decisions

Multi-Framework Support

Compatible with TensorFlow, PyTorch, ONNX, and more

Deploy diverse models without infrastructure changes

Hardware-Agnostic Optimization

Works across GPUs, TPUs, and CPU-based systems

Flexibility in hardware selection and cost optimization

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Enterprise Readiness

Role-Based Access Control

Workload Isolation

Audit Logging

Encryption in Transit

Resource Quotas & Rate Limiting

Integrations

7 total apps

Native Kubernetes integration for container orchestration and cluster management of inference workloads

Full support for TensorFlow models with optimized serving and inference acceleration

Seamless PyTorch model integration with automatic optimization and deployment support

Deep integration with NVIDIA GPUs for maximum performance and utilization optimization

Integration with AWS, Google Cloud, and Azure for hybrid inference deployment

Monitoring and observability integration for real-time inference metrics and performance tracking

ONNX model support enabling cross-framework model deployment and interoperability

AiDOOS Managed Deployment

Deploy Exafunction in

AiDOOS handles setup, CRM integration, SSO config, and user provisioning. Your team goes live — not your IT department.

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Deployments

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Adoption rate

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Post-deploy sat.

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Time to value

Prerequisites

Configuration Options

Virtual Delivery Center · A new delivery category

A Virtual Delivery Center for Exafunction

Pre-vetted experts and AI agents in the loop, assembled as a delivery pod. Pay in Delivery Units — universal pricing across roles, seniority, and tech stacks. No hiring, no contracting, no procurement cycle.

Plans from $2,000 — Starter Pack, 10 Delivery Units, 90 days
Refundable on unused Delivery Units, anytime — no questions asked
Re-delivery guarantee on acceptance miss
Pre-flight delivery sizing — you see the plan before you commit

Get a delivery plan for Exafunction What’s a Virtual Delivery Center?

How a Virtual Delivery Center delivers Exafunction

Outcome-based delivery via AiDOOS’s VDC model. Why VDC vs traditional consulting? →

Outcome-Based

Pay for results, not hours

Milestone-Driven

Clear deliverables at each phase

Expert Network

Access to certified specialists

Implementation Timeline

Discover

Requirements & assessment

Integrate

Setup & data migration

Validate

Testing & security audit

Rollout

Deployment & training

Optimize

Performance tuning

Schedule a Meeting

Frequently Asked Questions

What types of deep learning models does Exafunction support?

Exafunction supports models from TensorFlow, PyTorch, ONNX, and other major frameworks. It works with vision models, NLP models, recommendation systems, and custom architectures across CPU, GPU, and TPU hardware.

How much cost reduction can we expect?

Organizations typically achieve 35-75% infrastructure cost reductions depending on workload characteristics and current utilization rates. Many see up to 10x improvements in resource efficiency metrics.

What is the deployment timeline?

Exafunction can be deployed on existing Kubernetes clusters quickly. Initial setup typically takes 1-2 weeks for enterprise deployments, with AiDOOS marketplace providing managed deployment options to accelerate time-to-value.

Does Exafunction work in hybrid cloud environments?

Yes, Exafunction supports hybrid deployments across on-premises and cloud infrastructure, enabling consistent resource optimization across your entire inference infrastructure footprint.

How does Exafunction integrate with our existing monitoring?

Exafunction integrates with Prometheus, Grafana, and standard observability platforms. It provides detailed metrics on inference performance, resource utilization, and per-model costs for comprehensive visibility.

Can Exafunction help with cost attribution and chargeback?

Yes, Exafunction provides detailed per-model cost tracking and attribution, enabling accurate chargeback mechanisms for multi-tenant environments and cost center allocation.