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Private Beta

AI memory that stays
on your machine.

VeritasMemoria is a structured, auditable memory layer for AI-assisted workflows, built on a geometry-grounded knowledge graph that separates durable governance from active work. Every record is cryptographically signed and hash-chained. No cloud. No accounts. No telemetry.

Request Beta Access See How It Works
All data stored locally
HMAC-signed records
Works fully offline
Any LLM or none
Core Properties

Built different by design

Most memory systems trade transparency for convenience. VM trades neither — knowledge is organized by epistemic role and maturity, governed by explicit rules, and every change leaves a verifiable trace.

Local-First

All data stays on the machine running it. Nothing is sent to any server — not even to check for updates. Your memories are yours.

Tamper-Evident

Records are cryptographically signed and chained into a Merkle-verifiable audit trail. Retired memories move to an append-only archive rather than disappearing — you can always trace what changed, when, and why.

Human-in-the-Loop

The system cannot commit or retire memories without passing configurable oversight gates. You stay in control of what gets kept.

LLM-Agnostic

Works with OpenAI, Anthropic, Ollama, or any OpenAI-compatible endpoint. Runs fully offline in copy-paste mode with no LLM required.

Semantic Retrieval

Hybrid search combining dense vector embeddings and keyword indexing. Finds the right memory even when you don't remember exactly how you phrased it.

Transparent Storage

SQLite by default — a single file you can inspect, back up, or move. No opaque binary formats. Your data is always accessible without VM.

Isolated Matters, Shared Governance

Each project, case, or workstream lives in its own isolated space. Nothing crosses between them directly — shared policy and oversight live in one governed layer that every workstream defers to.

Regulatory-Grounded Permissions

Every action an agent can take is checked against layered permission rules tied to domain-specific compliance concerns — legal, medical, or financial — so higher-level policy can only restrict, never expand, what's allowed.

How It Works

Simple architecture, serious guarantees

Under the hood, knowledge is organized by role and maturity rather than dumped into one flat index — governance stays stable while active work and evidence can shift, and contested information is treated differently from settled information.

Step 1

You write a memory

Paste text, upload a document, or let an agent push context. VM assigns it to working memory.

Step 2

VM gates and signs it

Coherence and oversight checks run. On approval the record is HMAC-signed and appended to the hash chain.

Step 3

Retrieve it later

Semantic and keyword search surface the right context instantly. Pass it to any LLM or read it yourself.

Private Beta

Request beta access

VeritasMemoria is currently in private beta and isn't publicly available yet. Tell us a bit about your use case and we'll follow up by email.

Requests are sent directly to jessica@templetsolutions.com. We typically respond within a few business days.

LLM Support

Works with what you already use

Switch providers in a single line of config. Or skip the LLM entirely and run in copy-paste mode.

OpenAI Anthropic / Claude Ollama (local) Any OpenAI-compatible API Fully offline (copy-paste mode)
.env
# OpenAI
VM_LLM_PROVIDER=openai
VM_LLM_MODEL=gpt-4o
 
# Anthropic
VM_LLM_PROVIDER=anthropic
VM_LLM_MODEL=claude-sonnet-4-6
 
# Ollama (local, fully offline)
VM_LLM_PROVIDER=openai
VM_LLM_BASE_URL=http://localhost:11434/v1
 
# No LLM at all
VM_LLM_PROVIDER=copy_paste

Your data. Your machine. Your call.

VeritasMemoria ships blank and learns only what you explicitly give it. No defaults phoning home. No model training on your memories.

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