Deploy AI at 88 mph
The modern MLOps platform for engineering teams. Ship machine learning models faster, scale infrastructure effortlessly, and monitor everything in real-time. Where you’re going, you don’t need legacy infrastructure.
Deploy session
LiveShip sentiment-classifier v4 to production. Keep p95 under 100ms.
Detected PyTorch 2.4, 1.3 GB. Building on nvidia-t4, autoscaling 1 to 50 replicas.
Canary at 10% for 5 min: p95 47ms, errors 0.00%. Promoting to 100% — v4 is live.
Example session. Model names and timings are illustrative.
Backed by leading cloud infrastructure
- Microsoft Azure
- Google Cloud
- AWS
88x
Faster Deployment
99.9%
Uptime SLA
<50ms
P95 Latency
60%
Cost Reduction
Built for Modern AI Teams
Everything you need to ship ML models to production, without the infrastructure complexity.
Deploy any model—PyTorch, TensorFlow, Hugging Face, or custom—with a single command. No Kubernetes expertise required.
Track inference latency, model drift, and resource utilization. Get alerts before issues impact your users.
Automatically scale from zero to thousands of requests per second. Pay only for what you use.
SOC 2 Type II compliant. VPC isolation, encryption at rest and in transit, and comprehensive audit logs.
Canary deployments, shadow mode testing, and gradual rollouts. Ship with confidence, rollback instantly.
Smart instance selection, spot instance management, and GPU sharing. Reduce your cloud bill by up to 60%.
From Code to Production in Minutes
Stop wrestling with infrastructure. Our Flux engine handles the complexity so you can focus on building great models.
Connect Your Repository
Link your GitHub, GitLab, or Bitbucket repo. We detect your model framework automatically.
Configure & Deploy
Set your scaling parameters, select GPU types, and hit deploy. We handle the rest.
Monitor & Iterate
Real-time dashboards show performance metrics. Push updates with zero downtime.
# Deploy a model in seconds
from eightyeight import flux
# Initialize your model
model = flux.Model("gpt-custom")
# Deploy to production
model.deploy(
target="production",
auto_scale=True
)
# That's it. You're live.2.3M
Inferences/Day
47ms
Avg Latency
12
Active Models
$847
Saved This Week
Example workspace figures.
Built for Every AI Use Case
Whether you're deploying LLMs, computer vision models, or recommendation engines, 88mph scales with your needs.
Large Language Models
Deploy and fine-tune LLMs with optimized inference. Support for GPT, Llama, Mistral, and custom models with automatic batching.
Ready to accelerate your AI deployment?
Join engineering teams shipping models at 88 mph. Early access spots are limited.