SOVERE AI

Your code.Already in context.

A context manager for your engineering team. It indexes your repositories, internal libraries and design decisions, then gives the coding model the files and conventions each change needs.

See what it does

Your source code stays with you.

Code
Close-up of the two NVIDIA GPUs and precision metal cooling fins inside Sovere S2
Your repositories → useful codeIllustration

Designed for
regulated work.

Built for the way
your team builds.

Choose a Code workflow example

Build features using your existing patterns and internal libraries.

Add a retry policy using our existing client.Illustration

Use it all day.
No bill per token.

Sovere already knows your code, so a change reads 3 files, not 40. Included models have no per-token charges.

For scale: at Uber, heavy users of AI coding tools cost up to $2,000 a month each. Forbes, 17 May 2026.

One change, from request to review.Illustration

Works with the tools
you already use.

  • Claude Code
  • Codex
  • Cursor
  • Antigravity
  • GitHub Copilot
  • JetBrains
  • Zed

It starts with
your codebase.

Sovere indexes your repositories into a map of code, dependencies and design decisions. When someone asks for a change, the coding model starts with the relevant files and conventions instead of searching and re-reading the codebase.

  • Repositories
  • Internal libraries
  • Engineering standards
  • Design decisions

Approved repository changes refresh that context, so your team spends less time explaining the same code again.

How Sovere software works
Explore company adaptation
Files, people and decisions, connected.Illustration

Your first workflow.
A two-week target.

A pre-built model, adapted to your data and tested on the work your team needs to do.

Explore the setup timeline

Connect approved data, configure the workflow and agree the rules for your environment.

The two-week target begins when infrastructure, approved data and agreed integrations are ready. Hardware delivery and broader rollouts follow a separate schedule.

The right model.
The right system.

Code runs on the S-series configurations below. We’ll size the system around your workload.

Sovere S2 open black aluminum cube with two NVIDIA GPUs and blue front trim
NVIDIA GPUs
2
GPU memory
192 GB
Explore compatible systems

Recommended starting point

Sovere S2

A focused starting point for lighter coding assistance.

HardwareOne-time payment
$50,000
Software, model setup & first-year serviceIncluded in your initial purchase
$109,000
Total initial purchaseComplete system + first service year
$159,000
Annual managed AI serviceModel improvements, optimisation & support
$120,000per year, from year 2

Your first 12 months of managed AI service start at system acceptance and are included in the initial purchase. Annual renewal starts in year 2. Prices in USD, excluding tax. Your written quote confirms the configuration, service scope and any additional costs. See what’s included.

Explore S2

We size Code around the selected model, repository scope, context length and concurrent requests.

Full pricing details

About Code.

  • No. Code starts with an existing coding model and a prepared workflow. We connect approved repositories, adapt the system to your standards and test it on representative engineering tasks.

  • The coding model starts from a short brief: the component, the styles and the conventions involved. It skips the search and the re-reading, where most tokens go. Savings are largest on front-end, design and data work; backend edge cases still need fresh reasoning.

  • Yes. Claude Code, Codex, Cursor and other tools that can use a custom model endpoint connect through a standard model API. Supported features depend on each tool, and we confirm your tools during scoping.

  • The knowledge graph connects and refreshes repository context. Changing model weights is a separate process, used when it improves the agreed task. Your deployment scope makes that distinction clear.

  • Sovere hardware is the standard deployment. We can assess your own infrastructure against the model, GPU capacity, security requirements and integrations before agreeing a supported configuration.

  • We agree a set of real tasks from your codebase and evaluate correctness, tests and adherence to your standards. Any comparison with another model uses the same tasks and documented conditions.

  • Your team retains the review process. We agree repository access, permitted actions and approval gates as part of the setup.

VoiceDocumentsKnowledge

Bring the repository.
We’ll bring the AI.

Start with a real engineering task. We’ll scope the workflow, evaluation and system to run it.