AI product companies
You have an MCP server and a waiting list of enterprises who want it inside their own workspace. Every one of them is a bespoke integration project you did not plan for.
About Meetext
The hardest part of enterprise AI is not the model. It is the tenth customer.
Meetext is deployment infrastructure for software that has to run inside somebody else's workspace, with their credentials, under their security team's review, without one of your engineers on the call.
The thesis
FDE as a service.
The forward deployed engineer is the most valuable person at an enterprise AI company and the least scalable. They read the customer's environment, decide what the product should be allowed to do there, wire the credentials, prove it works, and stay reachable when it breaks. That work is real. It is also the same work every time, performed by hand, for a different customer.
So Meetext takes the repeated part. You connect a source once and approve a capability set once. Every customer after that installs themselves, validated the same way, monitored the same way, with a security review their team can read without a meeting.
A decision
Which operations are safe to expose in somebody else's workspace.
Rules, not judgment about the model.
A credential
Scoped to one tenant, resolvable by that tenant's name alone.
A naming scheme.
A proof
A real call, executed against the real installation, recorded.
Real calls with recorded outcomes.
A monitor
Something that notices when it stops working, before the customer does.
A loop.
Four artifacts. None of them requires judgment about the model. All of them require judgment about the boundary, and boundaries are what infrastructure is good at.
Who it is for
Anyone whose product has to land inside a customer.
Vertical SaaS with an API
Your customers keep asking for your product to show up where their teams already work. You have an OpenAPI document and no appetite for maintaining a Slack app per customer.
Teams whose founder is the FDE
Deployment currently means somebody senior on a call, reading a customer's workspace and wiring credentials by hand. It works, and it does not survive the tenth customer.
What it is not
Being narrow is the feature.
Meetext owns one unit: the customer deployment. Everything it refuses to own is why that one can be owned properly.
Not a workflow builder
There is no canvas, no triggers, no if-this-then-that. Meetext does not compose your product with other products. It ships your product into a place your customer controls.
Not a connector directory
A listing gets you discovered. It does not authorize a tenant, prove the install works, or tell you which of your customers is broken this morning.
Not an agent framework
The intelligence stays in your product. Meetext defines what leaves it, hosts the interface in front of it, and watches what happens next.
Where we actually are
We publish the honest version rather than the impressive one.
Atlassian, Google Workspace, HubSpot, Microsoft 365, Salesforce, ServiceNow and Slack are the destinations that install today, all of them in preview until a real provider deployment proves them. Everything else Meetext models is vocabulary in the type system and reports as planned until an adapter is registered. A new destination is seven methods and one registry line, and every registered adapter runs the same contract tests, so the second one is held to the standard of the first.
If your customers live somewhere we do not ship yet, tell us which and how many. That is how the next one gets picked.
2 environments free
Stop assigning an engineer to every customer.
Connect a source, publish, and send one link. Your next enterprise customer installs itself.
2 customer environments free, forever. No card required.