How to Choose an AI Enablement Platform: Questions to Ask Vendors
Choose an AI enablement platform by asking each vendor the same questions: which AI assistants it works with, whether agents use each person's own permissions, whether non-engineers can use it without config files, what each tool call record contains, where it can run, and how the price grows with users and tool calls. Ask for a live demo of a non-engineer connecting an app. Metorial answers each of these in its public docs and pricing page, and has a free plan to test them.
Vendor pages in this category make the same claims: secure, governed, enterprise-ready. The differences show up only when you ask specific questions and ask to see the answer working. These are the questions that separate them.
Which assistants does it work with?
A platform tied to one assistant makes every team standardize on it. Ask whether the same access works in Claude, ChatGPT, Cursor, and Copilot, and ask to see it. MCP-based platforms usually give each person one URL for all of them.
Whose permissions does the agent use?
Ask whether each person connects each app with their own account, or whether the platform uses a shared service account. Then ask to see a tool call record and find the person's name on it. Per-user access is what lets the app's own permissions apply.
Can non-engineers use it?
Ask for a demo where someone who does not write code connects an app and uses it in their assistant. If it involves a config file or an API key, AI will stay in engineering.
How is access managed?
Ask whether access is granted by group, whether groups come from your identity provider, and whether you can limit which tools each integration exposes. Ask how a team requests a new tool.
What does each record contain?
Look for the tool, the arguments, the result or error, the session, and the person or agent. Ask whether logs can be filtered and exported for an audit.
Where can it run?
Hosted, in your cloud, or on your own servers. Ask which options are on which plan, and ask for the SOC 2 Type II report.
How does the price grow?
Ask for the price for your first team and for the whole company. Seat prices, credit packs, and per-tool-call plans diverge quickly at scale.
How does Metorial answer these?
- Assistants. One Magic MCP URL per person for Claude, ChatGPT, Cursor, Copilot, and other MCP clients.
- Permissions. Each person connects apps with their own account through portals, and Tracing records the person on every call.
- Non-engineers. People sign in to a portal and connect apps with a click. Skills are written in a collaborative editor.
- Access. Allow or Deny per group on every integration and skill, with a chosen set of tools per integration. See Access control.
- Deployment. Hosted, or on-prem on the Enterprise plan. SOC 2 Type II and GDPR compliant.
- Price. Free Dev plan with 500K tool calls a month, Scale at $250 a month, and custom Enterprise. See pricing.
What Metorial does not do: it is not an AI assistant, a search index, or a model router. For those, see Best AI enablement platforms.
Frequently asked questions
What is the most revealing question to ask a vendor?
Ask them to show a tool call record and point to the person it ran for. If the record names a shared connection instead of a person, the platform is not per-user.
Should we run a proof of concept?
Yes, with one real team and two real apps for two weeks. A vendor demo on sample data will not show you what breaks.
How many integrations is enough?
Enough to cover the systems your first three teams use. Check those specific apps, and check that you can add your own or remote MCP servers for anything missing.
Does open source matter?
It matters if your security team wants to read the code or you must run it yourself. Obot is open source, and Metorial is open core under the FSL license.
How should we compare pricing?
Model the cost for your first team and for the whole company. Per-seat, per-credit, and per-tool-call prices look similar at small scale and very different at large scale.