FinOps & cloud cost management, cloud migration and disaster recovery

From infrastructure to AI, one question at a time

Hystax was founded in 2016 in Sunnyvale, California, by a team of cloud engineers and entrepreneurs who set out to make infrastructure easy to move and hard to break. Every product since has answered the next question our customers asked: first how to move and protect workloads, then how to control what the cloud costs, and now how to measure and govern the AI their teams use.

Three products, one principle: companies should have full control over what they run, what it costs and what it does, from a single virtual machine to an autonomous AI agent.

Control over what you run, what it costs and what it does

Every workload should be free to move between platforms without downtime or data loss. Every business should recover from an outage in minutes, not hours. Every dollar of cloud spend should be visible and justified. And every dollar of AI spend should be traceable to a delivered result, with every prompt and agent under control. That belief shapes what we build.

Hystax Platform

Live cloud migration, disaster recovery and cloud backup

One platform to move workloads between any source and any target and to keep them protected afterwards, built for enterprises and for MSPs serving thousands of customers.

Any-to-any replication with agent-based and agentless options
Unlimited test migrations, 1–3 minute cutovers
RPO in seconds, near-zero RTO, immutable backups
Multi-tenant partner portal, white-labeling, full RESTful API

Cloud migration Disaster recovery and backup

OptScale

FinOps and cloud cost optimization

Open-source platform for cost visibility, budgets, anomaly alerts and optimization recommendations across AWS, Azure, GCP, Alibaba Cloud and Kubernetes.

Apache 2.0 license, source on GitHub
Rightsizing, reserved-capacity and idle-resource recommendations
Budgets, TTL rules and Slack alerts that engage engineers

FinOps overview GitHub

OptScale AI

AI ROI and AI governance

Ties AI spend to delivered outcomes, routes and compresses model traffic to cut costs, enforces guardrails and data-loss prevention inline, and keeps AI agents within limits.