Your most private thoughts
are your most valuable currency.

Agentic AI Vector Memory Systems | Local-First MCP Memory Server. Your agent holds your ideas, strategies, and decisions the same cognitive currency you carry in your own mind. We built VEKTOR on a single conviction: synthetic memory deserves the same sanctity as biological memory.

PRIVACY ETHOS DOWNLOADS

Continuous updates included · No embedding costs · Open and frontier model choices · No DB lock-in

Slipstream

$9/month · Cancel any time · Commercial licence · Continuous updates · No embedding charges · No telemetry · No hidden fees · Open source tools included

SOLO

/month

1 licence key · Slipstream + Cloak + Faraday inclusive

1 licence key
Slipstream + Cloak
Faraday inclusive
Email support

Get Solo

TEAM

$35

/month

5 licence keys · All Core tools · Team licence all agents

5 licence keys
All Core tools included
Team licence all agents
Priority email support

Get Team

STUDIO

$59

/month

10 licence keys · Full Slipstream + Cloak · All future updates included

10 licence keys
Full Slipstream + Cloak
All future updates included
Priority email support

Get Studio

ENTERPRISE

$99+

/month

25 licence keys · Full Slipstream + Cloak · Custom terms

Full Slipstream + Cloak
All future updates included
Custom contract available
Priority email support

Get Enterprise

// ROI CALCULATOR

What does cloud memory
actually cost you? Run the math.

Adjust all four sliders to match your situation. Cloud subscription, embedding volume, time horizon, and team size VEKTOR auto-selects the right licence tier and shows you the real saving.

MONTHS 12 mo

CLOUD $/MO $40/mo

EMBED OPS ~500/day

USERS 1 user

VEKTOR TIER SOLO · $9/mo 1 user · 1 licence

CLOUD SUB

$480

EMBED FEES

$108

VEKTOR

// YOUR SAVING OVER THIS PERIOD

$429

Cloud total: $588
VEKTOR total: $9 monthly subscription.
Break-even: month 4

// NOTE Cloud subscription uses your entered $/month figure per user. Embedding fees estimated from public API pricing at selected daily volume. VEKTOR tier auto-selected: 1 user = Solo $9/mo · 2–5 users = Team $35/mo · 6–10 users = Studio $59/mo · 11+ users = Enterprise $99+/mo. Monthly subscription cancel any time. Figures are illustrative; actual costs vary by provider, model, and usage pattern. VEKTOR eliminates the memory subscription and dedicated embedding overhead LLM inference costs remain unchanged.

Questions? [email protected]

Why local-first wins.

Cloud memory vendors charge twice: a subscription for the service, and a per-call embedding fee on every store and recall. They also hold your data. VEKTOR eliminates both problems by architecture not policy.

Speed

~28ms

average recall

No API roundtrip. Vectors live on your machine. Recall is a local SQLite lookup not a network call to a cloud vendor’s infrastructure.

Cost

embedding cost

Cloud memory solutions bill per store and recall operation. At production volume those embedding fees often exceed the subscription itself. VEKTOR runs on your machine one flat price.

Sovereignty

100%

local · zero egress

Cloud vendors enforce compliance by policy. VEKTOR enforces it by architecture. Your MAGMA graph is a SQLite file on your machine structurally unreachable by any third party.

VEKTOR vs cloud memory vendors

Feature	VEKTOR	Cloud vendor memory
Recall latency	~28ms avg · <50ms p95	200–800ms
Data location	Your machine only	Vendor cloud servers
Embedding cost	$0 · fully local	Per-call API fee
GDPR / data residency	By architecture	Policy & certification only
EU AI Act / air-gap	Compliant by design	Requires vendor audit
Offline / no internet	Fully operational	Non-functional
Pricing model	$9/mo flat · one bill	Subscription + usage meter
Your data if you cancel	Yours · portable SQLite	Controlled on their servers

Your memory has a front door now. Faraday-Gate checks every visitor before they reach it.

Faraday-Gate is a transparent security proxy that sits between your agent and every other MCP server you run. It spawns and proxies your existing tool servers, scanning every schema and every call before anything reaches VEKTOR memory no changes to how you already work.

Tool schema scanning

SHA-256 tool pinning

Canary token tracking

Taint propagation

Human approval gate

Persistent audit trail

New MCP Tools
faraday_status · update_goal · approve_action

Live in v1.8.0 Preview

01 Static Scan

Every tool, checked on connect.

L0 signature scan

Tool names, descriptions, and input schemas are scanned against a signature library the moment a server connects. Sleeper patterns and known injection signatures are blocked before the agent ever sees the tool.

02 Tool Pinning

Rug-pulls get caught.

Phase C SHA-256 hash

Each tool's schema is hashed on first connect. If a server changes its tool definitions between sessions, the hash mismatch is flagged instantly and the tool is blocked closing the supply chain attack window.

03 Gate Queue

High-risk actions wait for you.

Human-in-the-loop approval

Actions that deviate from your stated goal or hit a risk threshold are held, not blocked. Review and approve or deny via faraday_status and faraday_approve_action nothing fires without sign-off.

"We don't respect your privacy.
We mathematically enforce it."

Respect is a promise. Architecture is a proof. VEKTOR is built on a local-first, air-gapped design where surveillance is physically impossible because we simply do not have access to your data.

GDPR by architecture

Zero data egress

Air-gap compatible

Data residency guaranteed

EU AI Act compliant

No third-party servers

Bytes of your
data on our servers

Architecturally impossible

01 Zero Knowledge

We cannot see your data.

By design.

No telemetry pipeline. No cloud sync. No anonymous aggregation. Your MAGMA graph is a SQLite file on your machine structurally inaccessible to us.

02 Informed Consent

Default state is silence.

Transmission requires opt-in.

No background pings. No opt-out flows buried in settings. If VEKTOR ever transmits anything beyond your machine, you explicitly chose it. Always.

03 Permanent Ownership

Your memory. Yours forever.

Cancel any time.

Your SQLite file is portable to any machine, unaffected by our pricing decisions or our continued existence. Sovereignty that survives us.

Biological Memory

Your Mind

Ideas & instincts

Strategies & decisions

Private by right

Same sanctity

Synthetic Memory

Your Agent

MAGMA graph · local SQLite

AUDN curation · zero leak

Private by architecture

The Law of Zero Knowledge we cannot see your data. By design.

Most AI infrastructure runs on an implicit bargain: capability in exchange for data. VEKTOR refuses this bargain. We ship the logic. You keep the data. Our servers have no access to your memory graph because we architecturally cannot. Zero knowledge is not a privacy setting. It is the absence of the mechanism that would allow us to know.

The Law of Informed Consent default state is silence. Transmission requires opt-in.

Every connection VEKTOR makes to the outside world requires active opt-in. No background pings. No anonymous telemetry dressed as "aggregate usage data." Consent is not a checkbox buried in an agreement. It is an architectural default off until you turn it on.

III

The Law of Permanent Ownership your SQLite file is yours. Forever. Without condition.

Subscriptions end. Companies pivot. APIs get deprecated. VEKTOR runs locally cancel any time and your SQLite file stays exactly where it is. Your memory data does not live on our servers. It cannot be held hostage because we do not hold it. Sovereignty means ownership that survives us.

The sanctity of mind, ported to silicon.

These are not marketing claims.
They are architectural commitments encoded into every layer of VEKTOR,
from the AUDN curation loop to the Cloak identity vault.

Read the full Privacy FAQ

VEKTOR Slipstream

The vector memory layer.

Local-first. Yours forever.

MAGMA graph · AUDN curation · local embeddings · zero cloud dependency

Every agent conversation produces raw context preferences, facts, corrections, plans. Slipstream captures all of it into a 4-layer associative graph that lives on your machine as a single SQLite file. When your agent asks what it knows, it gets ranked, scored, relationship-aware memories not a nearest-neighbour search across disconnected vectors.

Zero Embedding Cost

Slipstream runs local embeddings via bundled ONNX models. No OpenAI embedding bill. No per-token charge. 384-dimensional vectors, computed on your hardware, stored in your graph. Cost floor: $0.00/month.

MAGMA GRAPH · 4 LAYERS

01

LAYER_01

Semantic

Cosine similarity across all stored memories. Finds what's conceptually related not just keyword-matched. Ranked by importance score that decays over time.

SIMILARITY · RANKED

02

LAYER_02

Causal

Cause → Effect edges between memories. Your agent understands why things happened. Decision traces, error roots, action consequences all traversable.

CAUSE · EFFECT · WHY

03

LAYER_03

Temporal

Before → During → After sequences. Tracks how knowledge evolves across sessions. Recall when a preference changed, not just what the current preference is.

TIMELINE · DECAY · EVOLUTION

04

LAYER_04

Entity

Named entity co-occurrence. People, projects, technologies, events automatically linked by how often they appear together in memory.

PEOPLE · PROJECTS · EVENTS

AUDN CURATION LOOP

Every piece of context is evaluated before storage. AUDN asks: is this new information, a correction, a contradiction, or something already known? The result is a graph that stays clean without manual management zero duplicates, zero drift.

→

NEW INFO

ADD

→

CORRECTION

UPDATE

→

CONFLICT

DELETE

ALREADY KNOWN

NO_OP

LOCAL EMBEDDINGS

Monthly Embedding Cost

ONNX models, local compute, no API calls

384

Vector Dimensions

Full-fidelity, not quantized down

LLM Providers

Claude · OpenAI · Gemini · Groq · Mistral · Grok · DeepSeek · Together · Cohere · MiniMax · NVIDIA · Perplexity · LM Studio · LiteLLM · Ollama · OpenRouter

CORE METHODS

RECALL

memory.recall(query)

SEMANTIC

RANKED

Cosine similarity across the full MAGMA graph. Returns top-k memories ranked by combined importance score and vector similarity. Causal + temporal edges surfaced automatically.

REMEMBER

memory.remember(text)

AUDN

LOCAL EMBED

Routes input through the AUDN curation loop. Decides whether to ADD, UPDATE, DELETE, or NO_OP. Embeds locally. Stores in SQLite. No cloud roundtrip. Zero embedding cost.

GRAPH

memory.graph(node, {hops})

TRAVERSAL

Breadth-first traversal from a starting concept. Returns connected nodes and typed edges semantic / causal / temporal / entity up to N hops out.

DELTA

memory.delta(topic, days)

TEMPORAL

Returns what changed on a topic over a time window new nodes added, updates, contradictions resolved. Understand how your agent's knowledge evolved over time.

INCLUDED IN SLIPSTREAM

MAGMA 4-layer associative graph

AUDN curation loop

Local ONNX embeddings

LangChain v1 + v2 adapter

OpenAI Agents SDK integration

24 provider integrations

DXT-MCP Server 50+ tools for Claude Desktop

CrewAI adapter drop-in VektorMemory class

n8n node persistent memory in any workflow

Claude MCP Server full module

Mistral vektor_memoire · local bridge

3 production agent examples

FROM $9/MO

Single SQLite file your machine

No cloud. No per-call fees. No API key for memory.

All future Slipstream updates included

Local ONNX embeddings zero per-call embedding cost

Portable SQLite graph copy the file, migrate anywhere

Import / export tools for easy migration

Email support · typical response 24h

Commercial licence · production use

3 machines included per licence

Cancel any time no lock-in

Your data never leaves your machine

VEKTOR SLIPSTREAM

The full engine room.

REM. MCP. Visualizer.

Slipstream + REM dream cycle · Claude MCP server · D3 visualizer

Slipstream is the complete VEKTOR stack. REM compresses your agent's memory while it sleeps. The MCP server connects Claude Desktop to persistent memory in minutes. The D3 visualizer lets you see your agent's knowledge graph live.

REM Dream Cycle · 50:1 Compression 50 raw conversation fragments collapse into 3 distilled core insights. Noise dramatically reduced. Core signal retained. Runs via vektor rem from the CLI. Your agent wakes up smarter than when it went idle.

REM DREAM CYCLE · 7 PHASES

BEFORE REM · 50 FRAGMENTS

↓

up to

50:1

COMPRESSION

↓

7-PHASE CYCLE

Fragment collection

Duplicate detection

Contradiction resolution

Importance scoring

Cluster synthesis

Edge rewiring

Core insight extraction

SLIPSTREAM METHODS

REM

vektor rem

REM

up to 50:1

Triggers the 7-phase REM cycle manually. Compresses 50 fragments to 3 core insights. Also runs automatically via node rem.js when your agent is idle.

BRIEFING

memory.briefing()

SUMMARY

MORNING

Morning summary mode. Generates a structured brief of everything the agent learned in the past 24 hours distilled from the post-REM graph. Inject into system prompt at session start.

VISUALIZE

memory.visualize()

LIVE

Exports graph state to the D3 visualizer. See node clusters, edge weights, and importance decay in real time. Zoom into sub-graphs, filter by memory type, trace causal chains.

EXAMPLES

3 production agents

LANGCHAIN

MCP

Three complete production agent examples: LangChain researcher, OpenAI assistant loop, and a Claude MCP agent with full memory integration. Copy, adapt, ship.

Cloak · Sovereign Identity Layer

Your agent's identity.
Separate. Encrypted. Yours.

Memory is what an agent knows. Identity is who it is and what it can access. Cloak enforces this separation by design your SQLite memory graph and your encrypted passport vault are architecturally isolated. Share your memory backup freely. Your credentials stay locked to your machine.

Separation of Concerns: Cognition lives in the MAGMA graph. Identity lives in the Vault. A compromised memory backup cannot leak your session tokens, API keys, or GitHub credentials. The vault key is bound to your OS Keychain (macOS) or DPAPI (Windows) physically locked to one machine and one user account.

CLOAK_FETCH

cloak_fetch(url)

Fetches pages via the Accessibility Object Model the same tree a screen reader uses. Returns structured content without triggering fingerprint-based bot detection. Your agent sees the page. The server sees a browser.

AOM · STEALTH

CLOAK_PASSPORT

cloak_passport(key, value?)

Read and write to the encrypted ~/.vektor/vault.enc file. Stores session cookies, API keys, OAuth tokens. AES-256-GCM encrypted. Decryption key bound to OS Keychain unreadable on any other machine.

AES-256 · MACHINE-BOUND

CLOAK_DIFF

cloak_diff(a, b)

Structural diff between two page states, API responses, or text blobs. Returns added, removed, and changed sections as a structured object. Verify actions had expected effects. Detect session drift before it becomes a problem.

STRUCTURAL DIFF

TOKENS_SAVED

tokens_saved(session)

Logs token efficiency per session. Compares tokens consumed against what would have been used without VEKTOR memory compression. Produces an ROI audit trail hard proof the memory layer is paying for itself in inference cost reduction.

ROI AUDIT

CLOAK_RENDER NEW

cloak_render(url, selectors?)

High-fidelity layout sensor. Launches a headless browser, waits for fonts and scripts to load, then returns computed CSS, post-JS DOM state, bounding boxes, gap analysis, and asset errors. Your agent sees the page exactly as a human does after every script has run, every font has loaded, every layout has settled.

Sensor, not reader. Traditional fetch tools read raw HTML before scripts run. cloak_render waits for the full render cycle fonts loaded, JS executed, layout computed. What you get back is ground truth.

Works with any renderer React, Vue, Svelte, Astro, or plain static HTML. No framework-specific adapters required, no headless browser to manage yourself.

SSH TOOLS MOST POWERFUL

// cloak_ssh_exec(host, cmd) plan, approve, execute, rollback
"tier": "destructive",
"requires_approval": true,
"auto_backup": {
"ran": true,
"path": "~/backups/pre-change.tar.gz"
},
"rollback_key": "snap_8f21a",
"health_checks": ["nginx", "pm2"],
"status": "SUCCESS"

USE CASE

Remote server automation deploy, patch, restart services

USE CASE

Safe destructive ops every risky command auto-backed up first

USE CASE

Plan-then-approve agent proposes, human confirms before it runs

USE CASE

Instant rollback one call restores pre-change state

Cognition Layer

MAGMA graph · SQLite

AUDN curation loop

REM dream cycle

vektor_recall · vektor_store

vektor_graph · vektor_delta

Shareable. Backupable.
What the agent knows.

ISOLATED

Identity Layer

vault.enc · AES-256-GCM

OS Keychain / DPAPI binding

cloak_passport · credentials

cloak_fetch · AOM stealth

cloak_render · layout sensor

Machine-locked. Cannot leak.
Who the agent is.

How the vault works

cloak_passport reads and writes to a single encrypted file, vault.enc. Session cookies, API keys, and OAuth tokens all live there never in plaintext, never in your VEKTOR memory graph. Only cloak_passport can unlock it cloak_fetch and cloak_render read the web, but they never touch your credentials.

Encrypt

AES-256-GCM seals every credential before it touches disk

Bind

Decryption key is derived from your OS Keychain / DPAPI, never stored in the file

Isolate

A copied vault.enc is inert on any other machine the key never leaves yours

Vektor Slipstream

Pure recall.
Zero overhead.

Recall Latency · Local

~28ms avg recall

No API roundtrip. No cloud latency. Vectors live on your machine recall is a local SQLite lookup.

Embedding Cost

$1000

per embedding call

slipstream-embedder runs fully local. No OpenAI. No Cohere. No metered API. Embed once, recall forever.

DB Migration · No Lock-in

1011

migrating

0110

vex · migration CLI

slipstream-db is a standard SQLite file, not a proprietary format. Run vex migrate to move your vectors straight into Pinecone, Weaviate, Qdrant, Milvus, Chroma, or pgvector. Switch providers any time your data was never locked in.

Architecture · 3 Modules

slipstream-core

Spec-decoding retrieval engine. Bi-encoder shortlist + cross-encoder re-rank. HNSW index. Precision recall at ~28ms, fully local (CPU).

slipstream-embedder

Local embedding pipeline. Zero API cost. Runs on-device with no external dependencies.

slipstream-db

Lightweight SQLite vector store. Single file. Portable. Your memory graph is a standard SQLite file open in any SQLite browser, export to JSON, move to any machine. You own the data.

slipstream-core · slipstream-embedder

One query, five stages, fully on-device.

28ms precision recall, fully local

CPU no GPU, no external dependencies

$0 zero API cost to embed

Live Recall · slipstream-core

Precision without the graph overhead

Spec-decoding retrieval across your local vector store. Bi-encoder + cross-encoder. Results in milliseconds.

→ recall("coding preferences")

user prefers TypeScript over JavaScript0.97

avoid lodash use native array methods0.91

project uses ESM not CommonJS0.84

meeting with Sarah Friday 3pm0.22

Slipstream vs Traditional RAG

No cloud. No cost. No wait.

Feature	Slipstream	Cloud memory vendors
Recall latency	~28ms avg · <50ms p95	200–800ms
Embedding cost	$0 · fully local	Per-call API fee
Data location	Your machine	Vendor servers
GDPR / data residency	By architecture	Policy only
Air-gap / offline	Yes · SQLite local	No
Setup	npm install	SDK + API key + billing
Scales to	Millions of vectors	Depends on plan

Why Slipstream?

Your agent deserves
memory that moves at
hyper speed.

Most memory layers are designed for search engines, not agents.
Slipstream is purpose-built for the agent loop store, recall, done.
No embedding costs. No data stored. Sovereign architecture.

Recall latency comparison

VEKTOR local ~28ms

Cloud API 120ms+

4× faster · no round-trip · no billing

Just vectors. Fast.

Mistral Integration

Sovereign memory for Mistral agents.

VEKTOR connects to Mistral via a local HTTP bridge that ships inside the npm package. Your agent calls vektor_memoire the bridge runs on your machine, your memory never leaves it.

TOOL MANIFEST json

{
  "function": {
    "name": "vektor_memoire",
    "description": "Query VEKTOR sovereign memory graph.
Returns ranked memory fragments with
importance scores.",
    "parameters": {
      "action": { "type": "string" },
      "query":  { "type": "string" },
      "key":    { "type": "string" },
      "limit":  { "type": "integer", "default": 5 }
    },
    "required": ["action", "key"]
  }
}

SYSTEM PROMPT text

// Paste into Mistral / Le Chat agent

Tu es un assistant avec accès à une
mémoire persistante via vektor_memoire.

Utilise cet outil pour récupérer le
contexte pertinent avant de répondre.

Rappelle toujours avec query = sujet
principal de la question utilisateur.

// English version also supported
You have persistent memory via the
vektor_memoire tool. Always recall
before responding to any query.

STEP_01

Install Slipstream

Download the .tgz from Downloads and run npm install -g ./vektor-slipstream-1.8.0.tgz.

STEP_02

Activate Bridge

Run node node_modules/vektor-slipstream/mistral/mistral-setup.js. Enter your licence key. Bridge starts in 60 seconds.

STEP_03

Add Tool

Add vektor-tool-manifest.json as a tool in your Mistral agent or La Plateforme project.

STEP_04

Paste Prompt

Copy the system prompt printed by setup wizard. Paste into your Mistral agent. Memory is live.

SECURITY // LOCAL-FIRST

The Mistral bridge runs on your machine at localhost:3847 Mistral calls your local endpoint, not an external server. Your memory graph never leaves your machine. Licence validation is a Polar check on setup. Law I enforced: zero cloud routing of memory data.

Your most private thoughts
are your most valuable currency.

Slipstream

Why local-first wins.

The vector memory layer.

Local-first. Yours forever.

The full engine room.

REM. MCP. Visualizer.

Persistent Memory in Agentic AI Systems

What is the role of memory in an Agentic AI system?

Model Context Protocol (MCP) & Vektor

Advancing Sovereign AI in 2026

Memory Compression & the REM Dream Cycle

Your most private thoughts are your most valuable currency.

Slipstream

Why local-first wins.

The vector memory layer.

Local-first. Yours forever.

The full engine room.

REM. MCP. Visualizer.

Persistent Memory in Agentic AI Systems

What is the role of memory in an Agentic AI system?

Model Context Protocol (MCP) & Vektor

Advancing Sovereign AI in 2026

Memory Compression & the REM Dream Cycle

Your most private thoughts
are your most valuable currency.