How do their growth rates compare?

boat has a month-over-month growth rate of +520.8%; Union.ai has -28.4%.

How does pricing compare?

boat: Free Trial, Paid. Per-second billing with a $20/month minimum. The default 4 vCPU / 8 GB sandbox lists at $0.036/h, with smaller (2 vCPU / 4 GB) and larger (8 vCPU / 16 GB, 16 vCPU / 32 GB) sizes available. A 7-day free trial with a card provides 25 compute hours, and stopped sandboxes incur no compute charge while the disk is retained for at least 14 days. Union.ai: Freemium, Contact for Pricing. Freemium-style entry with a free open-source Flyte option. The managed Team plan starts at a $950/month minimum, fully credited to usage, with the first month free and no card required at signup. Consumption is metered on actions, vCPU-hours, memory GB-hours and GPU-hours across published volume bands. Enterprise is custom-priced on an annual commit with volume discounts, and optional Union-managed clusters cost $500 per cluster per month, capped at $2,500.

What are alternatives to boat and Union.ai?

Other tools in related categories include RunPod, Together AI, Vast.ai, Browser Use, Modal.

boat vs Union.ai — Traffic (66.87K vs 17.79K), Pricing & Verdict

Open AI Tools

boat vs Union.ai — Traffic (66.87K vs 17.79K), Pricing & Verdict | Open AI Tools

Side-by-Side Traffic & Specification Matrix

Dimension / Metric	boat	Union.ai
Official Domain	boat.dev	union.ai
Pricing Model	Free Trial, Paid	Freemium, Contact for Pricing
Monthly Visits	66.87K (66,870)	17.79K (17,787)
MoM Traffic Delta	+56.1K (+520.8%)	-7.04K (-28.4%)
Primary Market & Share	🇺🇸 United States (76.3%)	🇺🇸 United States (52.8%)
Direct Visits / mo	37.78K	7.04K
User Rating	4.6	4.4
Supported Platforms	Website	Website

boat

Persistent Ubuntu cloud VMs built for AI agent factories

Persistent full Linux VMs

Each sandbox is a complete Ubuntu machine with systemd, Docker, databases, and cron, so anything that runs on Linux runs here.

Fast snapshot forking

Clone a configured sandbox from a disk snapshot in seconds to launch large fleets of identical parallel agents.

SSH, SCP, and virtual desktop

Connect over SSH and SCP or open a 60fps virtual desktop and browser to inspect web apps, IDEs, and 3D scenes.

API, CLI, and SDKs

Drive everything programmatically through the boat CLI (with --json output), an HTTP API, or Python and TypeScript SDKs.

Strengths & Pros

+Full Ubuntu VMs rather than restricted containers, with Docker and systemd included
+Very fast disk-level forking makes large parallel agent runs affordable
+Transparent per-second pricing with no compute charge while stopped

Limitations

–No GPU option and no US or Asia data regions

Frequently Asked Questions: boat vs Union.ai

boat has 66,870 monthly visits, while Union.ai has 17,787. Traffic estimates describe audience size, not product quality.

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Union.ai

The durable AI runtime that runs in your cloud, not ours

Durable execution engine

Tasks, traces and artifacts survive infrastructure failure. Runs fork, recover and replay from the last good step instead of starting over, with retries and caching handled by the runtime.

AI factory and artifact lineage

Named, typed and versioned artifacts wire teams together, with lineage showing which run produced each version and which downstream tasks consume it.

Sovereign, bring-your-own-cloud deployment

Run the control plane in Union's cloud while workloads execute on clusters in your AWS, GCP, Azure or neocloud account, under your own security perimeter.

Production agents and agent traceability

Bring OpenAI, Claude, PydanticAI or CrewAI agents; each turn is traced and sandboxed in ephemeral containers, MCP servers and human approvals supported.

Strengths & Pros

+Durable execution means long training, inference and agent runs survive node loss, spot reclamation and API rate limits
+Bring-your-own-cloud architecture keeps data, models and secrets inside your own security perimeter
+Backed by the creators of Flyte, so the open-source engine and the managed platform evolve together
+Transparent published rate card with marginal volume bands for actions, CPU, memory and GPU
+Strong fit for GPU-heavy work: multi-node training, HPO sweeps, batch inference and zero-to-scale LLM serving

Limitations

–The Team plan carries a $950/month minimum that is only credited back as usage, so it is a poor fit for hobbyists or very small experiments
–Because workloads run inside your own cloud, you still pay your cloud provider for compute on top of Union's metering
–Setup expects a Kubernetes cluster and familiarity with Python task environments, which raises the bar for non-engineering users
–Rate-card pricing across four meters (actions, vCPU, memory, GPU) can be hard to forecast without monitoring
–PyTorch, Ray and agent integrations are powerful but the ecosystem is still narrower than some general-purpose orchestrators