# ibl.ai vs Vercel AI SDK

> Source: https://ibl.ai/resources/comparisons/self-hosted-ai-vs-vercel-ai-sdk
> Last updated: 2026-10-20


*A free, Apache-2.0 TypeScript toolkit for calling models and streaming them into a UI, or an owned platform that supplies the agents, memory, data and governance behind that UI*

**On ibl.ai you own all the code and the data, run it model-agnostic across any LLM, and pay with no per-seat pricing — so you can deploy anywhere, from your own cloud to a fully air-gapped network.**

## What's the difference between ibl.ai and Vercel AI SDK?

The Vercel AI SDK is Apache-2.0 and free, so you already own the toolkit code. With ibl.ai you own all the code and the data for the layer underneath it as well: the agents, memories, datasets, evals and audit logs your UI talks to.

These two overlap less than the names suggest. The AI SDK is a provider-agnostic TypeScript library: one API over many model providers, streaming hooks such as useChat for React, Svelte and Vue, and a ToolLoopAgent for tool-calling loops.

What it deliberately leaves to you is state: who the user is, what the agent remembers, which documents it may retrieve, how it is evaluated and who may change it. Vercel's AI Gateway routes tokens at list price with no markup, but it is a hosted service.

ibl.ai supplies that state on infrastructure you control. It is model-agnostic, has no per-seat pricing, and deploys anywhere: your cloud, a VPC, on-premise or air-gapped. ibl.ai is family-owned and operated from New York, NY.

## How do ibl.ai and the Vercel AI SDK compare feature by feature?

### Ownership & Deployment

| Criteria | ibl.ai | Vercel AI SDK |
|----------|--------------------|--------------------|
| Source code you receive | Platform source under license; the OS frontend and the vibe skills are MIT on GitHub. | Apache-2.0 on GitHub (27.4K stars, October 2026), free to use and modify. |
| Where the backend runs | Your AWS or GCP account via infra-cli, any existing server, or air-gapped. | Anywhere Node runs — the SDK is a library. AI Gateway, if you use it, is Vercel-hosted. |
| Where state and data live | Conversations, memories, datasets and traces in the database you operate. | Wherever you build it — the SDK stores nothing, so persistence is your design. |
| Pricing shape | Usage-based with no per-seat pricing, against caps you set. | SDK free; AI Gateway charges provider list price with no markup, including bring-your-own-key. |

### Developer Experience

| Criteria | ibl.ai | Vercel AI SDK |
|----------|--------------------|--------------------|
| Streaming UI primitives | A drop-in Chat component with streaming, canvas, files and voice, rendered in-process. | The reference implementation: useChat and generative UI hooks across Next.js, React, Svelte and Vue. |
| Provider breadth in code | Provider cards include Amazon, Anthropic, Google, Microsoft, NVIDIA, OpenAI and xAI. | First-party packages for OpenAI, Anthropic, Google, Mistral, Cohere, Groq, xAI and more, plus any OpenAI-compatible server. |
| Bring-your-own UI freedom | Use the SDK components, or call the REST API, SSE or WebSocket from any UI. | Unopinionated by design — every pixel is yours. |

### What Ships Behind the UI

| Criteria | ibl.ai | Vercel AI SDK |
|----------|--------------------|--------------------|
| Agent memory | Global and agent-specific memories in PGVector, five default categories, REST API. | Not included; you choose and wire a store. |
| RAG over your documents | Datasets from files, URLs, crawls, Drive, OneDrive and GitHub on a retrain schedule. | Embedding helpers are included; ingestion, vector store and re-indexing are yours. |
| Evals, RBAC & audit | LLM-as-Judge benchmarks, roles and policies, SSO, SCIM and per-agent audit logs. | Out of scope for a UI and model toolkit. |

## Where does the Vercel AI SDK win, and where does ibl.ai?

### Is the Vercel AI SDK a competitor to ibl.ai at all?

**ibl.ai:** ibl.ai is the backend: agents, memory, data, evaluation and governance, deployed on your infrastructure and reachable over REST, SSE, WebSocket and MCP.

**Vercel AI SDK:** The AI SDK is the client-and-server toolkit for calling models and streaming results into an interface, with no persistence of its own.

**Verdict:** Mostly they stack rather than compete. The real choice is whether you build the backend state layer yourself or run one you own.

### Which has better streaming UI and provider support?

**ibl.ai:** ibl.ai's Chat component is complete but opinionated, and its provider list is curated per organization rather than a package per vendor.

**Vercel AI SDK:** The AI SDK is the best-in-class TypeScript toolkit here: useChat, typed tool calls, structured output and first-party packages for a long list of providers.

**Verdict:** The AI SDK wins on interface primitives and provider breadth in code. Keep it for the UI if your team already uses it.

### What do I still have to build with the AI SDK?

**ibl.ai:** With ibl.ai, memory, document ingestion, evals, access control, spend caps and audit come with the platform and work across every configured model.

**Vercel AI SDK:** With the AI SDK alone, each of those is a service you design, host and secure — often the larger share of a production AI feature.

**Verdict:** Count the state layer, not the hooks. That is where the engineering time and the compliance exposure live.

## Should my team use the Vercel AI SDK, ibl.ai, or both?

### Product teams adding one AI feature to an existing app — Vercel AI SDK

If the feature is stateless or your app already stores what it needs, the AI SDK is the lightest correct tool.

### Organizations running many agents for many users — ibl.ai

Shared memory, datasets, evals, RBAC and audit across every agent are what a toolkit leaves out and a platform provides.

### Regulated or air-gapped deployments — ibl.ai

The whole backend installs inside your perimeter, so no hosted gateway sits in the data path.

### Next.js teams that like their AI SDK frontend — Either

Keep the AI SDK in the UI and put ibl.ai behind it. ibl.ai's own hosting API deploys apps to Vercel, so the two already meet.

## How do I migrate from the Vercel AI SDK to ibl.ai?

### Vercel AI SDK → ibl.ai (low difficulty)

Timeline: One to four weeks, depending on how much state your app already stores

- Agents: a ToolLoopAgent's system prompt, model and tools become an ibl.ai agent created over the API or with the iblai-api-agent-create skill.
- Model calls: ibl.ai serves an OpenAI-compatible /v1/chat/completions endpoint routed to any provider/model — the shape the AI SDK's openai-compatible provider is built to call.
- Tools: tools defined with tool() become MCP servers the agent connects to over WebSocket or Streamable HTTP.
- Memory and RAG: replace your own message store and vector index with ibl.ai sessions, memories and datasets.
- UI: keep useChat, or swap in the ibl.ai Chat component from @iblai/iblai-js; scaffold a new app with the vibe skills.
- Eval & deployment: load test questions as benchmarks, then run the platform with infra-cli while the frontend deploys wherever it does today.

Docs and skills for this move:

- [Getting started with Agentic Vibe](/developer/vibe/getting-started)
- [Skill: iblai-api-inference](/developer/skills/iblai-api-inference)
- [Skill: iblai-vibe-agent-chat](/developer/skills/iblai-vibe-agent-chat)
- [Skill: iblai-vibe-scaffold](/developer/skills/iblai-vibe-scaffold)
- [Connect an MCP server](/developer/platform/mcp/mcp-connections)
- [Agent memory](/developer/platform/agents/memory)
- [Skill: iblai-api-agent-dataset](/developer/skills/iblai-api-agent-dataset)
- [Deploy with infra-cli](/developer/infra-cli)

### ibl.ai → Vercel AI SDK only (medium difficulty)

Timeline: Days for the UI, weeks for the state layer

- Prompts and settings read out over the REST API; chat history and evaluation results export as files.
- Design a persistence layer for conversations, memories and retrieval before cutting over.
- Rebuild permissions, audit and spend controls in your application.
- Reasonable when the use case shrinks to a stateless feature inside one product.

## FAQ

**Q: Is the Vercel AI SDK open source?**

Yes. The AI SDK is Apache-2.0 licensed and free. Vercel's AI Gateway, which it can route through, is a hosted Vercel service that charges provider list price with no markup on tokens.

**Q: Can I use the Vercel AI SDK with ibl.ai?**

Yes, as a frontend. ibl.ai exposes REST, SSE, WebSocket and an OpenAI-compatible completions endpoint, so an AI SDK interface can sit in front of agents, memory and data that run on your deployment.

**Q: Does the Vercel AI SDK store conversations or memory?**

No. The SDK is stateless by design: it calls models and streams results. Conversation storage, long-term memory and retrieval indexes are services you add.

**Q: Does ibl.ai charge per seat?**

No. ibl.ai has no per-seat pricing; you pay by usage against caps you set per organization, agent or user.

**Q: When is the Vercel AI SDK enough on its own?**

When the AI feature is stateless, one product owns it, and your app already handles users and data. Then a toolkit is the right size and a platform would be overhead.

**Q: How does ibl.ai fit alongside the Vercel AI SDK?**

On ibl.ai you own all the code and the data behind your interface, run any model and deploy anywhere, while the AI SDK can keep rendering the front end.


## Where do these facts come from?

1. The AI SDK is a free, open-source, provider-agnostic TypeScript toolkit with useChat UI hooks and a ToolLoopAgent class. [vercel/ai on GitHub](https://github.com/vercel/ai)
2. The AI SDK is licensed under the Apache License, Version 2.0. [vercel/ai LICENSE](https://github.com/vercel/ai/blob/main/LICENSE)
3. First-party providers include OpenAI, Anthropic, Google, Mistral, Cohere, Groq, xAI and DeepSeek, plus community providers. [AI SDK docs: Providers](https://ai-sdk.dev/providers/ai-sdk-providers)
4. The @ai-sdk/openai-compatible package connects the SDK to any provider that implements the OpenAI API. [AI SDK docs: OpenAI-compatible providers](https://ai-sdk.dev/providers/openai-compatible-providers)
5. AI Gateway charges no markup and no platform fee on tokens, including with bring-your-own-key, and team-wide zero data retention costs $0.10 per 1,000 requests. [Vercel docs: AI Gateway pricing](https://vercel.com/docs/ai-gateway/pricing)


## Where does ibl.ai fit alongside Vercel AI SDK?

**ibl.ai is the agentic AI platform where you own all the code and the data. You self-host the entire stack inside your own perimeter, run it model-agnostic across any LLM and switch anytime, and pay by usage with no per-seat pricing — so you can deploy anywhere: your cloud, on-premise, GovCloud, or fully air-gapped.**

ibl.ai is the state layer an AI SDK app eventually needs: agents, memory, datasets, evaluation, RBAC and audit, deployed on infrastructure you control and reachable from any TypeScript frontend.

Agentic OS is the platform; Agentic Vibe gives coding agents 157 skills, including a Next.js scaffold and a drop-in Chat component. You own all the code and the data and can keep the AI SDK in the UI where it is strongest.

- **You own all the code and the data.** Full source code under a perpetual license, running on your infrastructure. Not API access to someone else's platform — the stack itself is yours.
- **Model-agnostic.** Run any LLM — Claude, GPT, Gemini, Llama, Command, or your own fine-tune — and switch providers without rewriting the platform.
- **No per-seat pricing.** Usage-based billing against a budget cap you set. Cost tracks what your organization actually uses, not how many people you employ.
- **Deploy anywhere.** Your cloud, your VPC, on-premise, GovCloud, or a fully air-gapped network with no outbound connectivity.

1.6M+ users across 400+ organizations run the platform this way, including NVIDIA, MIT, and Syracuse University.

ibl.ai is family-owned and operated from New York, NY — a U.S.-headquartered, domestically-owned long-term partner, not a vendor that sells licenses and moves on.