Deterministic O(1) recall. Millisecond response. 100% local. Zero token waste.
Works with Claude Code · Cursor · VS Code · Any MCP Client
Every time your AI agent encounters a question it answered yesterday, it re-reads the entire context from scratch. A 50,000-token document queried 20 times generates 980,000 redundant tokens — and you pay for every one of them.
RAG pipelines approximate. Vector search guesses. Context windows overflow and forget. The industry calls this "good enough." We call it a 70-80% production failure rate.
GrantAi doesn't search. It recalls. Milliseconds. Exact. Every time.
| RAG Pipeline | Vector Search | GrantAi | |
|---|---|---|---|
| Recall Speed | ~800ms+ | ~200ms | Milliseconds |
| Accuracy | Approximate | Approximate | Deterministic |
| Architecture | Chunk → Embed → Retrieve → Rerank | Embed → ANN Search | O(1) Direct Lookup |
| Token Overhead | Re-reads full context | Re-embeds on query | Zero redundant tokens |
| Data Location | Cloud required | Cloud typical | 100% local |
Introduces the Retrieval Tax: the hidden cost enterprises pay for probabilistic memory systems. Klarna's $60M reversal, the $37B enterprise AI spend, and the architecture that breaks the pattern.
Read the paperIntroduces MAC-F, the Mergers and Acquisitions Cybersecurity Framework used by boards, acquirers, and deal teams to price and manage cyber risk in transactions.
Get the bookWhen agents need to coordinate, they need shared context. GrantAi is the memory layer that lets your agents work together.
Agent A discovers something. Agent B queries the brain and has it instantly. No re-embedding. No context window stuffing. No middleware.
Speaker attribution built in. Filter memories by agent: researcher, analyst, writer. Full provenance for every piece of knowledge.
Session 1: Research agent stores findings. Session 2: Writing agent recalls them. Context persists across sessions, agents, and workflows.
The brain IS the coordination layer. Agents read and write to shared memory. No message queues. No state machines. Just deterministic recall.
LangChain. CrewAI. AutoGen. One brain.
Not probabilistic search. O(1) lookup against a deterministic knowledge ledger. If it was stored, it will be recalled — exactly as stored, every time.
Your data never leaves your machine. No cloud sync. No telemetry. AES-256 encrypted at rest. Architecture designed for SOC 2, HIPAA, and SEC 17a-4 requirements.
Claude Code, Cursor, Windsurf, VS Code — every MCP-compatible tool shares one memory. Context follows you across sessions, projects, and workflows.
Your AI reads context once and remembers it. No re-reading, no re-embedding, no redundant inference. Every token you spend creates lasting knowledge.
If it is stored, it can be recalled.
We Guarantee Grounding.
Download and run the installer for your platform.
See full installation guide for license key setup.
Add the MCP server to Claude Desktop, Claude Code, Cursor, or any MCP client.
{
"mcpServers": {
"grantai": {
"command": "sh",
"args": ["-c", "docker run -i --rm --pull always -v grantai-data:/data ghcr.io/solonai-com/grantai-memory:1.9.6"]
}
}
}Your AI remembers everything. Ask about past conversations, code, decisions — recalled in milliseconds.
ALM, Harvard University. Founder and CEO of SolonAI.
18 years architecting security and compliance for financial institutions managing over $13 trillion in assets. Bank of America, JPMorgan Chase, and Citi among them.
I designed the first security and compliance architecture for an AI company operating under SEC 17a-4. No industry blueprint existed. I wrote one. That architecture passed due diligence for Goldman Sachs, Vanguard, Vista Equity Partners, Blackstone, and TIAA.
I built GrantAi because every AI memory layer I evaluated failed every audit bar I ever set.
Enterprise AI deserves better than "close enough."
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