Why Server-Blind AI Storage?

FLASH’s mission is to be the first line of privacy protection while AI is created. Most “AI databases” store embeddings in the cloud and send prompts to remote LLMs. The server — or the vendor — can see your documents, queries, and agent memory.

FLASH inverts this model. Default flash-zk is strong. You keep the key; you can weaken the engine if you choose to. Mission & responsibility.

---

The Problem

Your documents  →  Cloud vector DB  →  Plaintext embeddings + metadata visible
Your questions  →  Remote LLM API    →  Query + context logged
Agent memory    →  SaaS memory layer →  Third-party retention policies

Even with “encryption at rest,” the service operator typically holds keys or sees decrypted payloads at query time.

---

The FLASH Model

Your documents  →  Client encrypts  →  Server stores ciphertext + trapdoors only
Your RAG query  →  Client embeds      →  Similarity over encrypted vectors
Agent memory    →  Local FLASH vault  →  Encrypted episodic recall

The engine answers: “Which trapdoor / vector ID matches?” — never “What does the user’s document say?”

---

Three Workloads, One Layer

1. Private RAG

Ingest PDFs, notes, or medical records. Ask questions semantically. The storage layer never holds plaintext.

const rag = client.privateRAG("clinical");
await rag.ingest({ title: "Protocol", text: "..." });
const ctx = await rag.ask("contraindications?");

2. Agent Memory

Agents need persistent context. FLASH stores memories encrypted with importance scores and TTL — not in a vendor’s conversation log.

const memory = client.agentMemory("assistant");
await memory.remember("User prefers Arabic UI", { importance: 2 });

3. Sealed Vault

API keys and secrets in an isolated domain with passphrase lock — separate from general collections.

const vault = client.sealedVault("secrets");
vault.unlock("passphrase");
await vault.put("openai_key", { value: "sk-..." });

---

When Server-Blind Matters

Industry	Risk without server-blind storage
Healthcare	PHI exposure in vector indexes
Legal	Privileged documents in cloud RAG
Finance	Client data in LLM context logs
Personal AI	Notes and journals on third-party servers

---

What FLASH Is Not

• Not a chatbot — flashsh ask retrieves encrypted chunks, it does not call OpenAI
• Not “encryption optional” — zero-knowledge envelopes are architectural
• Not a plugin for another database — FLASH is a standalone engine

---

Get Started

1. Mission & responsibility — who owns protection, the app, and the key
2. Do this first — seal the key this week
3. Positioning — when to choose FLASH
4. Private RAG — ingest + ask workflow
5. LangChain Integration — connect AI frameworks
6. Intelligence Console — local web UI