Priostack
Agent Context Network Developers Request early access
Priostack · Agent Context Network

One memory. Every AI. Yours.

Your AI agents forget everything between sessions, and every new tool starts from zero. The Agent Context Network gives them one place to remember, and it works with any AI model. You own it, you decide who can use it, and agents only pull the piece they need.

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Works with Claude, ChatGPT, and your own models. You own the data, we never train on it, and you can export or delete it any time.

One memory, every model
Claudeconnected
ChatGPTconnected
Your agentsconnected
all share↓
Your memory
you own it · you set the rules
01 The problem

Every session starts from zero.

AI agents do not remember. Close the chat and it is gone, so you paste the same background in again and again. The usual fix bolts on a system that pours more and more text into the model as your data grows, which makes every answer slower and more expensive. Either way, your knowledge ends up trapped inside one assistant, one vendor, one session.

02 What you get

A memory you actually control.

Store once, use anywhere

Save what your agents learn one time. Use it again from Claude, ChatGPT, your own models, or whatever you switch to next. Your memory does not belong to any one AI company.

You own it, you set the rules

Decide who can read it, who can add to it, and what they are allowed to do with it. Share a slice with a partner, keep the rest private, and revoke access any time.

Agents pull only what they need

Instead of dumping your whole knowledge base into the model, an agent asks for the relevant piece and gets a short, focused answer. Fast and affordable, even as your memory grows into the millions of items.

It will not make things up

Answers come from what is actually saved. When something is not in your memory, it says so, instead of guessing.

Every access is on the record

See which agent read what, when, and under which permission. Nothing happens to your data quietly.

Turn it into a product soon

Later, publish part of your memory and let other people's agents pay to use it. Your knowledge becomes an asset instead of a cost.

03 Who it is for

Built for teams running real agents.

If more than one agent, or more than one person, needs to work from the same knowledge, this is for you. A few of the ways teams put it to work:

Support and operations

Every agent answers from the same policies, past tickets, and product facts. Update it once and they all stay current, instead of drifting apart.

Research and analysis

Give analyst agents a shared, permissioned library. They draw only from what you approved, and you can see exactly what was read for each answer.

Multi-agent products

Many agents, one memory. What one agent learns is there for the next, with no long transcripts passed back and forth between them.

Knowledge owners

Sitting on valuable know-how? Keep it private, share a slice with a partner under clear terms, and later let other people's agents pay to use it.

04 How it works

Connect. Remember. Stay in control.

01

Connect any agent

Your agents connect over MCP, the open standard for plugging AI into tools. No lock-in, no custom glue.

02

Store what matters

Documents, facts, decisions, past conversations. Anything worth remembering goes into your own space.

03

Agents ask, and get a focused answer

They request what is relevant to the task and receive a short, permission-checked reply, not a data dump.

04

You stay in control

Set permissions, watch usage, and change your mind whenever you want. Export or delete on your terms.

05 See it in action

A question in. A grounded answer out.

Put a few facts into a space. When an agent asks, it gets a short answer drawn straight from them, with the source noted. Ask about something you never stored, and it tells you so instead of inventing an answer.

You store
Refunds past 30 days need a manager code.
policy
The self-serve plan has no phone support.
policy
ACME reported slow exports in the EU region.
observation
An agent asks
"Can I refund an order from six weeks ago?"
question
answered from your memory↓
Yes, with a manager approval code.
source: your refund policy
"What is ACME's contract value?"
not in memory, so it says: I do not have that.
06 Why it stays cheap

Fast and affordable, no matter how big it gets.

A typical setup sends the AI more and more as your data grows, so your bills climb with your knowledge. We send a small, relevant slice instead, so speed and cost stay flat whether you store a thousand items or a million.

A typical setup: what the AI has to read as your data grows

More data means more for the model to read, every single time.

With the Agent Context Network
A small,
steady slice

Whether your memory holds a thousand items or a million, each answer stays about the same size. Your costs do not balloon with your knowledge.

Any model
Claude, ChatGPT, your own
Milliseconds
to answer a typical request
Thousands
of requests handled at once
100% yours
export or delete any time
07 Trust

It only tells you what it actually knows.

The Agent Context Network answers from your saved memory and nothing else. If the answer is not there, it says so, instead of inventing one. You can trust what comes back, because it came from what you put in.

And it is yours. We do not read your context to train anything, we cannot sell it, and no one you did not authorize can touch it. Export or delete it whenever you want.

Yours
export or delete any time
Never trained on
your context is not our training data
Grounded
answers only from what you stored
08 Questions

The things people ask first.

Which AI models does it work with?+
Any model that speaks MCP, the open standard for connecting AI to tools. Claude, ChatGPT, and your own models all use the same memory. Nothing is tied to one vendor, so you keep your memory when you switch.
Do you train on my data?+
No. We do not read your context to train anything, and we cannot sell it. It stays yours, and you can export or delete it whenever you want.
What happens when the answer is not in my memory?+
It tells you it does not know, instead of guessing. Answers come from what you actually stored, so you can trust what comes back.
How am I billed?+
On what your agents do, not on what you store. Each plan includes a monthly allowance of questions. Beyond it, you pay a flat rate for the amount of context actually examined to answer, never for the small reply that is sent back.
Can I share part of my memory with a partner?+
Yes. Grant a specific space with the exact rights you choose, set how long anything may be kept, and revoke access at any time. Later, you will be able to charge for access.
Do I need to understand how it is stored?+
No. You store items and ask questions. Everything underneath is handled for you, and it keeps improving without changing how you build.
Is it available now?+
It is in preview. Request early access and we will set you up with a key and a free sandbox to try it.
09 Pricing

Simple plans. Pay for what you use.

Every plan gives you your own memory, your own spaces, and permissions you control. You are billed on what your agents actually do, never on the size of what you store.

Starter
€149 / month

For a solo builder or a first project.

  • One private space for a focused knowledge base
  • Your own agents, connected over MCP
  • A monthly allowance of questions included
  • Permissions, access logs, and receipts
Growth Popular
€349 / month

For a team that shares context across agents.

  • A larger memory for a real corpus
  • Up to five separate spaces
  • More agents and a higher monthly allowance
  • Sharing, fine-grained rights, and a usage dashboard
Scale
€999 / month

For a business running many agents on a large corpus.

  • An enterprise-scale memory
  • Many spaces and agents
  • Priority allowance and overage rate
  • The controls and support a larger team needs

Go over your monthly usage? You only pay for the extra, at a flat rate, and only on what agents actually use, never on what you store. Every plan starts with a free sandbox. Preview pricing: plans and limits may change before general availability.

10 For developers

Everything you need to build on it.

Connect over MCP and drive it with plain HTTP calls. Read the deep dive for the why, follow the tutorial for the how, and manage every space, grant and receipt from the console.

Deep dive

The memory layer, explained

What an Agent Context Network is, how grounded answers work, and why speed and cost stay flat as it grows.

Read the article →
Tutorial · 10 min

Build your first space

Connect, create a space, store context, grant an agent, run a query, and read the receipt. Copy and paste, top to bottom.

Start the tutorial →

Bring your agents. Keep your memory.

The Agent Context Network is in preview. Tell us what your agents need to remember, and we will get you a key.

Request early access Talk to us on Telegram

Any model · You own the data · Pay for what agents use