Eight apps, one AI, one dataset.
Website, forms, email, Knowledge Base, CRM, chat, a developer portal and socials, run by one AI over the same contact and content records. Each app page says what it replaces, what it produces and where its edges are.
Pick an app
Open any of the eight to see what it replaces, what it produces and where its edges are.
What the gaps between tools cost
Each of these tools is fine on its own. The cost sits between them: the form that has never seen the CRM, the email tool that cannot tell what a contact read, the chat bot that has never opened the docs. Here every app reads the same records.
Separate tools | Giant Context | |
|---|---|---|
Website | A CMS with pages someone builds and forgets to update. | The AI drafts the pages and proposes updates when the product changes. You approve each one. |
Lists you build by hand, in a tool that cannot see your site or your CRM. | The AI writes the email. Mind picks the recipients from what each contact did. | |
Support | A scripted bot that has never read your docs, and an inbox behind it. | Chat answers from the Knowledge Base the AI keeps current, and hands off to a person with a drafted reply. |
Contacts | A CRM that knows what your team typed into it. | A record every app writes to and the AI reads before it drafts anything. |
By the numbers
0
integrated apps
0
MCP tools
0
API operations
0
AI clients that connect over MCP
What one dataset makes possible
A form submission lands on a CRM record. The AI reads that record before it drafts the email. A chat question is answered from the Knowledge Base the AI keeps current. Nothing is copied between tools because there is one set of records.
One price for all eight
$25 per million tokens of AI work. Every app, every seat, no tiers. Nothing during alpha.
Usage-based pricing
Start with the app that hurts most
Ask for early access. Run one app for a few weeks and let the other seven read what it learns.