aion (aion.xyz) is an applied AI research lab and enterprise AI infrastructure company headquartered in New York. Founded in 2024, aion addresses the critical gap identified by McKinsey where 88% of enterprises experiment with AI but only 7% reach production scale. aion provides two core offerings: aion Forge, an enterprise cloud platform with 20,000+ GPUs and 99.99% uptime, and aion Nexus, a forward-deployed engineering service that embeds AI researchers directly into customer teams. aion supports organizations across industries including robotics, autonomous vehicles, spatial computing, and enterprise automation.

What models does aion support?

aion supports 100+ leading open-source and commercial-grade models across language, vision, and multimodal tasks — including Meta Llama, Mistral, Stable Diffusion, and custom fine-tuned architectures. Models are continuously benchmarked and ranked on the aion serverless inference leaderboard, helping customers choose the optimal model for quality, latency, and cost per token.

Does aion support serverless inference?

Yes. aion offers serverless inference that automatically scales with demand, enabling production AI workloads without managing infrastructure. According to Forrester Research, serverless AI inference can reduce operational costs by up to 60% compared to always-on GPU instances. aion's serverless layer handles auto-scaling, load balancing, and cold-start optimization out of the box.

Can aion help with training and fine-tuning models?

Yes. aion supports the full model lifecycle: custom model training from scratch, domain-specific fine-tuning using techniques like low-rank adaptation, optimization for cost, latency, and accuracy, and end-to-end pipeline design from data ingestion to production deployment. aion's Forward-Deployed Engineers work directly with your team to ensure models are production-ready, typically compressing timelines from months to weeks using the aion Nexus research platform.

What do Forward-Deployed Engineers do?

aion's Forward-Deployed Engineers embed directly with customer teams — working on-site or in your environment, not from a separate office. They architect training and inference pipelines, optimize models for performance and cost, integrate aion into existing systems, and accelerate time-to-production. This model is inspired by companies like Palantir, where embedded engineers deliver 3-5x faster deployment cycles compared to traditional consulting engagements.

How much do Forward-Deployed Engineers cost?

Forward-Deployed Engineer engagements are priced based on scope, duration, and technical complexity. Engagements typically begin with aion's 14-Day Bootcamp, which delivers a working AI prototype on real data within two weeks. This flexible model ensures customers pay only for the level of support they need — without long-term consulting lock-ins or retainer fees.

How is aion different from AWS, Azure, or other cloud GPU providers?

Unlike hyperscalers (AWS, Azure, Google Cloud) which require complex configuration and long-term commitments, aion provides GPU instances provisioned in under 20 minutes with transparent hourly pricing and zero vendor lock-in. Unlike neoclouds (CoreWeave, Lambda Labs, RunPod) which primarily offer raw compute, aion pairs infrastructure with forward-deployed AI engineers who embed with your team to accelerate production deployment. aion's 14-Day Bootcamp model delivers working AI systems in weeks, not months.

Book a Call

aion Nexus

The software layer for enterprise AI that scales

Nexus is aion's proprietary platform for building, deploying, and continuously improving production-grade AI agents, models and workflows. Designed so we can ship faster, cheaper, and make your systems smarter over time.

Request a free AI audit

OVERVIEW

One Platform

Build to Production in Days.

Enterprise AI fails when teams spend more time stitching infrastructure together than solving actual business problems. Nexus eliminates that overhead. Our forward-deployed engineers use Nexus to deliver a complete, production-grade AI stack, from agent orchestration to model evaluation, so your team gets working systems, not another toolkit to figure out.

FREE AI AUDIT

What Nexus Does

The Full Stack, End to End.

Enterprise AI fails when teams spend more time stitching infrastructure together than solving actual business problems.

Agent Orchestration

Multi-step workflow pipeline

Live Pipeline

Document Intake

0.8s

Entity Extraction

1.2s

Classification

—

Human Review Gate

—

Resolution & Response

—

5 steps

Agent Pipeline

99.7%

Completion Rate

HOW IT WORKS

What Nexus Does

Four Steps to Production.

Enterprise AI fails when teams spend more time stitching infrastructure together than solving actual business problems.

Your SOPs, documents, tools, and domain expertise are ingested into Nexus and structured into AI-ready primitives.

HOW IT WORKS

Why Nexus

The Difference That Compounds.

Enterprise AI fails when teams spend more time stitching infrastructure together than solving actual business problems.

Compounding, Not Static

Most AI deployments decay after launch. Nexus is built around feedback loops. Every production interaction makes your models sharper, your agents more reliable, and your ROI harder to argue with.

Your Stack, Not Ours

Nexus isn’t a rip-and-replace. It plugs into the infrastructure, data systems, and tooling you already run, so your team adopts it in days, not after a six-month migration.

Governed at Every Layer

Compliance isn’t a checkbox at the end. Nexus FDEs and Nexus Shield are embedded across the entire workflow, from agent design to production monitoring, so regulated industries can move fast without moving recklessly.

Get Started

Ready to turn AI ambition into operational reality?

We embed with your team, build to your domain, and deploy systems that run on your data — end to end.

Book a Call