Self-hosted AI that knows your code, your docs and your designs.

From Figma to GitLab

Every answer cites the file it came from. Open-weight models run on your own GPU server: your code never leaves your infrastructure.

Apply for the pilot How it keeps your code private
shop-platformExample · invented codebase
How does checkout apply a discount code?

The customer enters the code in the promo field on the payment step [3]. applyDiscount() checks that it exists, has not expired and that the basket meets the minimum, then subtracts the amount before tax [1].

Percentage codes are capped, and only one code applies per order [2].

Sources
[1]codecheckout/discounts.tsL12–31
[2]docdocs/pricing-rules.md
[3]figmaCheckout / Promo code

isobata noun

A private knowledge layer for your software: one layer that knows your code, your documentation and your designs, runs on your own servers, and answers your team's questions with the sources.

Why a knowledge layer

It sits between your team and everything that describes your system, so a question gets one answer that draws on code, docs and designs together, instead of a search in three places.

The name

In Italian, an isobata is an isobath: the line on a sea chart that joins points of equal depth, mapping what lies below the surface.

Knowing how your own system works takes too long, and cloud AI is not an option for your code.

The answer is spread out

Part of it is in one repository, part in the docs, part in a Figma file nobody linked.

The person who knows is busy, or gone

Questions wait on the one engineer who wrote it, or on nobody at all.

Your code can't go to an AI cloud

Client contracts or regulators forbid sending it to a third-party AI service, so most assistants are ruled out.

Verifiable answers, not guesses.

Each part of the answer above points to a source. Open it and you see the code, the rule in the docs and the screen in Figma that it came from.

[1]checkout/discounts.ts
export function applyDiscount(cart, code) {
  const rule = findRule(code);
  if (!rule || rule.expiresAt < now())
    return reject("invalid");
  if (cart.subtotal < rule.minBasket)
    return reject("min_basket");
  const amount = rule.type === "percent"
    ? Math.min(cart.subtotal * rule.value, rule.cap)
    : rule.value;
  // applied before tax
  return { ...cart, discount: amount };
}
[2]docs/pricing-rules.md
Promo codes

One code per order. A second code replaces the first.

Percentage codes are capped at the cap set on the rule.

Discounts are applied to the subtotal, before VAT.

[3]Checkout / Promo code
Subtotal€84.00
SPRING20
Apply
Discount−€16.80
Total before VAT€67.20

Illustrative example. The codebase, files and design are invented.

Connect, index, ask, all on your servers.

  1. 1

    Connect

    Point isobata at your GitLab projects (cloud or self-managed), your Figma files and the Markdown docs in your repositories.

  2. 2

    Index

    It reads the code, documentation and designs on your own server.

  3. 3

    Ask

    Your team asks in a chat and gets answers that list the files and frames they come from.

Included in the pilotGitHub repositories, and PDF documents such as specifications and manuals, cited down to the page.

Nothing leaves your infrastructure.

Not your code, not your questions, not your answers.

Security and architecture, in detail →
  • Self-hostedInstalled in your cloud (VPC) or on-premises, on a single GPU server you control.
  • Open-weight models on your own GPUNo third-party AI provider and no external AI API. The models run next to your code.
  • Never trained on your codeWe never see your code, your questions or the answers.
  • Outbound calls only to hosts you allowYou set the allowlist, and every outbound call is logged.
  • A Docker image, security checks already passedisobata ships as a Docker image you run in your VPC. Every release is signed and vulnerability-scanned before we publish it, and verified again before it installs.
  • Nothing reports backThe licence is checked offline on your server. No telemetry.

Shape it with us.

Who it suits

An engineering team on GitLab or GitHub, with code it cannot send to a cloud service.

What you get

Help with installation, and direct contact with the people building isobata.

Pilot duration and terms to be confirmed.

What you need

A Linux server with one NVIDIA GPU. Requirements and installation

Opens an email to pilot@isobata.ai with your answers. Nothing is stored on this site.

Questions

What is isobata?

A private knowledge layer for your software: one layer that reads your code, documentation and designs on your own servers and answers your team's questions, citing every source.

Which AI models does it use?

Open-weight models that run on your own GPU server: Qwen3 and Qwen2.5-Coder, with an embedding model and a re-ranker, all Apache 2.0. No third-party AI provider or external AI API is involved. More on the models

What can you see of our code?

Nothing. Your code, questions and answers stay on your servers. The licence is checked offline and there is no telemetry.

What hardware do we need?

A Linux server with one NVIDIA GPU with 24 GB of memory, in your cloud account or data centre. Full requirements

Does it work with GitHub?

Yes. GitHub is included in the pilot, alongside GitLab, cloud and self-managed. Tell us which you use when you apply.

Can it read PDF documents?

Yes. Your Markdown documentation, and PDF documents such as specifications and manuals, cited down to the page, are included in the pilot.

How much does it cost?

isobata is licensed per installation, by year. Pilot terms on request.