Never re-explain yourself again.
Your AI forgets everything between sessions. Your preferences, your patterns, your project decisions — all gone. grāmatr℠ fixes that. It learns how you work and carries that intelligence across every AI tool you use. 40,000 tokens down to 1,200 — 97% reduction. Better responses. Lower costs.
Two breakthroughs. The floor rose — twice.
52 weeks of public GitHub data. Two architectural breakthroughs — each one permanently raised the productivity baseline. Not a one-week spike. Sustained, compounding output visible in every week that followed.
Contribution activity is publicly disclosed on GitHub. This is not a demo — it is production data.
The floor rose. Twice.
One developer, one GitHub history, two distinct step-changes — both driven by patent-pending context-engineering breakthroughs.
November 16, 2025: 816 contributions in a single week — the highest single week in the dataset, the first proof the brain worked.
March 24–31, 2026: 607 commits, 1,203 files, 354,489 lines added — the second step-change, layered on the first. Feature branches. Pull requests. Code review. CI/CD. 15 tagged production releases shipped through a single grāmatr℠ skill that automates version bump through Kubernetes rollout.
The industry tradeoff has always been: ship fast or ship clean. grāmatr makes you stop choosing.
Every AI tool has the same problem.
It forgets. Not sometimes. Every single time.
Developers lose afternoons rebuilding context their AI had yesterday. Writers watch months of relationship-building with their AI vanish overnight. Teams watch institutional knowledge evaporate every time someone closes a session. You build context over hours or weeks, and then it's gone.
"Claude Code becomes a brilliant stranger who needs to rediscover everything."
— Niels, co-founder of Emelia
"The context you built up — the decisions, the dead ends, the 'wait, we tried that and it failed because…' — evaporates."
— decker, developer
"Fred has no idea who Fred is. 'I'm ChatGPT,' it says. Zombie Fred has FORGOTTEN EVERYTHING that has come before."
— BMLWrites, novelist
This isn't a niche complaint from power users. The data confirms it's an industry-wide crisis — and it's getting worse, not better.
"Context engineering is the delicate art and science of filling the context window with just the right information for the next step."
"I really like the term 'context engineering' over prompt engineering. It describes the core skill better."
"Building with language models is becoming less about finding the right words for your prompts, and more about answering the broader question of 'what configuration of context is most likely to generate our model's desired behavior?'"
The people building AI agree: the problem isn't the models. It's context engineering — getting the right information to the models at the right time. grāmatr automates that entire process.
Not memory. Intelligence.
Every AI context tool on the market stores your old conversations and retrieves them unchanged. grāmatr does something fundamentally different. It learns from your interactions and gets measurably smarter over time — then carries that intelligence everywhere you work.
Learns
Your AI gets smarter from every interaction — actually learning your preferences, your patterns, the way you make decisions. One developer's system went from needing 40,000 tokens of instructions to 1,200 — with better results. That's not compression. That's intelligence.
Routes
Every request gets pre-classified by trained models in milliseconds before expensive models see it. Effort level, intent, relevant context — resolved before a single API call is made. The result: faster responses, lower costs, and an AI that sends exactly what's needed instead of everything it knows.
Unifies
One brain across every AI tool. Claude, ChatGPT, Gemini, Cursor, Codex — your intelligence travels with you. If a better model launches next month, switch to it. No re-explaining. No vendor lock-in.
Evolves
Creates new capabilities from how you work. Real usage patterns become deployable skills that ship without redeploying anything. Two skills currently in production were learned this way: WriteWebsite (which generated this site) and DeployGramatr (which automates production deployment). For teams, admins control what's shared. One person's discovery compounds across the organization.
Context engineering, automated.
grāmatr runs a continuous intelligence pipeline — not a storage system. Every interaction teaches it something new. Every lesson makes the next interaction faster, more accurate, and less expensive.
Your AI doesn't just remember what you said last week. It learns your preferences, your patterns, and your decision-making style — and delivers better results with less re-explanation every session.
Learn how the intelligence pipeline works →Choose your path.
For Individuals
You use AI every day — and every day, you waste 10 to 30 minutes re-explaining your codebase, your preferences, your project context. grāmatr makes your AI remember you across sessions and across tools. Install in 60 seconds.
See what changes for you →For Teams
Knowledge walks out the door when people leave. grāmatr gives your team shared AI intelligence — patterns, conventions, and capabilities that persist no matter who joins or leaves. Admin controls keep things private.
See what changes for your team →For Enterprise
Every session starts cold. No cross-platform governance. No way to measure ROI. grāmatr provides tiered training controls, measurable token savings, and intelligence that compounds across your organization — with user-isolated encryption at every level.
See the enterprise story →Your AI should know you by now.
Stop starting from zero. grāmatr learns how you work, gets smarter from every interaction, and carries that intelligence everywhere you go — across tools, across sessions, across your entire team. The private beta is open.