Your AI. Your way.
grāmatr learns your preferences, your patterns, and your decision-making style — then carries that intelligence into every AI tool you use. Claude, ChatGPT, Gemini, Cursor. One brain. Every tool. Yours.
Every AI you use starts from zero.
You know this routine. You open a new session, and the AI that helped you build an entire feature yesterday has no idea who you are. Your codebase, your conventions, your preferences — gone. Every single time.
"Explicitly instructed Claude Code to use my name and email for Git commits. 30 minutes later, Claude Code attempted to push with username 'claude' and email '[email protected]'. When questioned, acted as if no previous Git configuration instructions existed."
— @SDS-Mike, developer · GitHub Issue #2545
That is not a minor inconvenience. That is explicit instructions being discarded within minutes of a single session. And it compounds across sessions.
"By the fourth or fifth interaction, Claude Code starts ignoring your rules. It stops asking for confirmation. It forgets your workflow preferences. It's like your CLAUDE.md instructions never existed."
— Siddhant Khare, developer · DEV Community
The reality is that this frustration has a measurable cost. Not just annoyance — actual lost productivity, every day.
"You lose between 10 and 30 minutes at the start of each session rebuilding context. Over a work week, that adds up to several hours of lost productivity."
— Niels, co-founder of Emelia · emelia.io
Several hours a week, spent telling your AI the same things you told it yesterday. That is not a workflow problem. That is a missing context engineering layer.
What changes on Monday.
You start your morning by re-explaining your project structure. You paste in your coding conventions — again. By the third interaction, the AI has already forgotten the architectural decisions you made an hour ago. By the fifth, it is ignoring your CLAUDE.md rules entirely.
Your system prompt has ballooned to 40,000 tokens because that is the only way to get the AI to behave consistently. And even then, corrections do not stick. You fix the same mistake on Tuesday that you fixed on Monday. The AI is not learning from your interactions — it is processing them and moving on.
Your AI remembers yesterday. It knows your project structure, your naming conventions, and the architectural decision you made last Thursday about separating test agents from coding agents. When you corrected its approach to error handling on Monday, that correction became a permanent pattern.
The 40,000-token system prompt you were maintaining? Replaced by a 1,200-token intelligence packet that actually performs better. Not because the information was compressed, but because grāmatr learned what matters to you and delivers only that. Your preferences persist across sessions. Your corrections compound into lasting improvement.
Get started in 60 seconds.
Setting up grāmatr is three steps, regardless of your tool.
For developers (Claude Code, Cursor, and other MCP-compatible tools):
Install
Add grāmatr as an MCP server to your development environment. One config line.
Connect
Authenticate with your grāmatr account. Your intelligence layer activates immediately.
Work
There is no step three. grāmatr learns as you go. No manual configuration, no rules to write, no prompts to maintain.
For everyone else: Sign up at app.gramatr.com and connect your AI tools through the web dashboard. Same intelligence, same learning, no command line required.
Works with everything you use.
grāmatr is not locked to a single platform. Your intelligence travels with you across every AI tool in your workflow.
One brain. Every tool. Start a conversation in Claude Code, pick it up in ChatGPT, check something in Gemini — your AI already knows what you need in each one.
Your data is yours.
Here is what happens with your interactions: they train your AI. Only your AI. Nobody else's.
grāmatr encrypts your data at the user level. Row-level isolation means your patterns, preferences, and corrections exist in a space that is invisible to every other user on the platform. Even grāmatr staff cannot access your data. There is no shared training pool, no cross-user blending, no model improvement happening behind the scenes with your information.
Your interactions make your AI smarter. That intelligence belongs to you — encrypted, isolated, and private at every level.
Getting started.
grāmatr is in private beta. Personal tier includes all four pillars — learning, routing, cross-platform intelligence, and dynamic skill creation — with per-user encryption and full data isolation. Pricing is available upon approval. Request early access to see tier details and founding-member pricing.
Ready to stop re-explaining yourself?
Your AI should know you by now. Request Early Access
See how it works, explore grāmatr for Teams, or view pricing.