Can you run AI agents on Vercel?
Vercel supports building and running AI agents, from model access and code execution to long-running agent logic.
This article covers what Vercel provides for building and executing AI agents, where the current limits sit for production agent workloads, and what alternatives are worth considering.
- Yes. Vercel provides the AI SDK for model access, Sandbox for isolated code execution, and Workflows for agent logic that needs to pause and resume across longer tasks.
- Vercel Sandbox runs in a single region (
iad1, US East) and has no GPU option. - Vercel's BYOC option deploys to AWS only and is currently in Private Beta as of July 2026, and its newer enterprise identity and credential controls are also in Beta or Private Beta.
- For agent workloads that need multi-region execution, GPU-enabled sandboxes, or BYOC across multiple clouds, platforms like Northflank provide that today.
Running AI agents in production: what enterprises need beyond a demo
Enterprises building AI agents for production, not demos, need more than a place to run code. They need tenant isolation by default, compliance certifications, multi-cloud deployment, and infrastructure a small team can operate without a dedicated infrastructure team.
Northflank provides this today: SOC 2 Type II and HIPAA compliance, BYOC across several cloud providers and 600+ regions, on-premises deployment via BYOK, GPU-enabled sandboxes, and every workload, service, job, and build, isolated by default with no shared runtime or filesystem between tenants.
Versaia, an agent orchestration platform serving enterprise, healthcare, and local government customers in the EU, moved off AWS onto Northflank and cut compute costs 60% while increasing voice agent throughput 4x.
Get started (self-serve) or book a demo if you're evaluating BYOC or GPU capacity for an agent platform. Read the Versaia case study
An AI agent workload typically needs four things from its underlying platform: a way to call language models, a way to execute code the model generates or requests, a way to maintain state across multiple steps, and a way to reach external systems with scoped credentials.
How a platform handles each of these determines whether it fits a given agent workload, from a single-purpose chatbot to a multi-step autonomous agent that writes and runs its own code.
Vercel provides dedicated products for model access, code execution, and state and durability:
| Requirement | Vercel product | What it does |
|---|---|---|
| Model calls | AI SDK, AI Gateway | AI SDK is a TypeScript toolkit for text generation, tool calling, and agent patterns. AI Gateway routes requests to multiple models through one endpoint. |
| Code execution | Vercel Sandbox | Runs untrusted or AI-generated code inside isolated microVMs, with Node.js and Python runtimes. |
| State and durability | Workflows | Lets agent logic pause and resume across longer tasks, surviving deployments and crashes. |
Not fully, and not yet broadly. Vercel introduced bring-your-own-cloud (BYOC) as part of its June 16, 2026 Enterprise Apps and Agents announcement. It runs compute, build artifacts, and run data inside a customer's own AWS account and VPC, with Vercel operating the control plane on top.
Vercel's BYOC currently supports only AWS and is in Private Beta, so it isn't yet available as a self-serve option.
Teams needing multi-cloud or immediate BYOC access can look at platform alternatives like Northflank's BYOC.
For a breakdown of BYOC options by cloud provider and availability, see the best BYOC alternatives to Vercel. On why this matters specifically for enterprise AI tooling, why smart enterprises are insisting on BYOC for AI tools covers the compliance and data-residency drivers behind that requirement.
Several constraints matter specifically for agent workloads, as opposed to typical frontend deployments.
| Limit | Detail |
|---|---|
| Sandbox region | Vercel Sandbox runs only in iad1 (US East) |
| GPU support | Vercel Sandbox has no GPU option; it's built for CPU-bound code execution. |
| BYOC availability | AWS only, Private Beta, not self-serve. |
| Sandbox session cost | Vercel Sandbox includes 5 hours/month of Active CPU free on Hobby; Pro and Enterprise are billed $0.128/hour, with a maximum runtime of 45 minutes on Hobby versus 24 hours on Pro and Enterprise. |
For a closer look at how Vercel Sandbox's isolation and session limits compare to other sandboxing approaches, see best sandbox runners for AI agents, which compares session length, region availability, and BYOC support across providers, and best code execution sandbox for AI agents, which breaks down isolation models for running untrusted or AI-generated code.
Northflank is built enterprise-first, with SOC 2 Type II and HIPAA compliance and BYOC across several cloud providers and 600+ regions. Its self-serve developer experience has also made it a common choice for startups building AI agent products without a dedicated platform team.
Yavendio is one example: a 15-person engineering team building AI-powered WhatsApp sales agents for over 7,000 e-commerce customers across Latin America, with no dedicated DevOps function. They use Northflank's BYOC model to deploy across AWS and Azure, draining existing startup cloud credits while running their LangGraph-based agents with automated CI/CD, zero-downtime deployments, and horizontal autoscaling.
Where this differs from Vercel's current agent stack:
- BYOC is generally available today, across AWS, GCP, Azure, Oracle, Civo, and CoreWeave, plus bare-metal and on-premises deployment via Bring Your Own Kubernetes (BYOK).
- Sandboxes support GPUs directly, including A100, H100, H200, and B200 instances, for agent workloads that need inference or training compute alongside code execution.
- Sandboxes run across multiple regions, on Northflank's managed cloud or inside a customer's own cluster, rather than a single fixed region.
- Sandboxes are ephemeral by default but persistent with no forced time limit when state needs to survive across sessions, with attachable volumes and managed databases running alongside them.
- Agent-native operations tooling is available through Northflank Skills, a public, installable agent skill for Claude Code, Cursor, and other editors that lets an AI agent deploy and operate services, jobs, sandboxes, and GPU workloads on Northflank directly.
For teams estimating cost across a mix of services, GPUs, and BYOC clusters, the pricing calculator provides a monthly estimate based on actual workload configuration. For a broader look at platforms built specifically for GPU-backed agent execution, see GPU sandboxes explained.
Get started (self-serve) to try Northflank's compute and sandbox pricing directly, or book a demo if you're scoping a BYOC or GPU deployment for an enterprise agent platform. See Northflank for Enterprise for details on SOC 2, HIPAA, SSO, and forward-deployed control plane options.
No. Vercel Sandbox is built for CPU-bound code execution and does not currently offer a GPU option. If you're looking for an alternative, Northflank supports GPU-enabled sandboxes directly, including A100, H100, and H200 instances.
Vercel's BYOC on AWS is in Private Beta as of the June 16, 2026 announcement, meaning it isn't a self-serve option and requires contacting Vercel directly.
No. Vercel Agent is a dashboard-based assistant for code review and production investigation on Vercel's own platform. Building an agent into an application uses the AI SDK, AI Gateway, Sandbox, and Workflows instead.
No. Vercel Sandbox runs only in the iad1 (US East) region.
Northflank is an enterprise-grade alternative with BYOC available across AWS, GCP, Azure, Oracle, Civo, and CoreWeave today, compared to Vercel's AWS-only, Private Beta BYOC.
- Best agent cloud platforms: a comparison of platforms built for deploying and orchestrating AI agents in production, beyond single-purpose sandboxing tools.
- What is an AI sandbox?: covers the isolation models (containers, microVMs, gVisor) that underpin safe AI code execution.
- Ephemeral execution environments for AI agents: explains when ephemeral versus persistent execution environments fit different agent workloads.
- How to sandbox AI agents: a practical guide to isolating agent-generated code from production systems and credentials.
- Multi-cloud orchestration for AI workloads: looks at running AI workloads across multiple cloud providers without re-platforming.
- Best persistent sandbox platforms: compares platforms that support long-lived, stateful sandbox sessions for agents that need memory across runs.
