Open a session in your browser. Chat with the AI on one side, a full VSCode IDE on the other, a real git repo backing the workspace. Describe what you need in plain language. The AI writes PyInfra code as commits you can read, edit, and diff. Dry-runs are free. Applying needs two humans. Your data never leaves your network.
Non inultus premor
I am not injured unavenged.
30+
French hospitals hit by ransomware in 2022-2023
20%
of hospital servers run obsolete, unpatched systems
150+
hours/month on manual vulnerability management
3x
increase in vulnerability exploitation as initial access vector
30+ French hospitals hit by ransomware in 2 years. 20% of hospital servers run obsolete systems. Your team spends 150h/month on manual patching instead of securing the fleet.
60% of breaches trace to a known, unpatched vulnerability. Vulnerability exploitation as initial access vector tripled in one year. Every delay is a window for attackers.
Claude Code and Cursor shell out to bash. They run arbitrary commands. One hallucinated rm -rf and the business is down. No sysadmin trusts an AI with raw SSH to production.
NIS2 covers 15,000 entities in France alone. DORA, HDS, SecNumCloud: compliance deadlines are here. Manual patching cannot keep up. Auditors are knocking.
Government, banks, hospitals cannot send fleet data to a SaaS vendor. 86% of CIOs plan to repatriate workloads on-premises in 2025 (IDC). Existing AI copilots are cloud-only. That is a dealbreaker.
Open a session in your browser. Chat with the AI on one side, an embedded VSCode IDE on the other. The AI writes PyInfra code into a real git repo. You run a dry-run for free. Applying requires a teammate to approve, and they have to be a different user.
Query your infrastructure in plain language. The AI collects PyInfra facts across your fleet and returns structured data: OS versions, installed packages, running services, kernel versions, open ports. Every call is logged in the session audit trail.
"Harden the prod-web group against CIS Level 1." The AI reads the docs library (PyInfra ops, regulations, examples), fetches facts, and writes real PyInfra code as commits in your session's git repo. You see every file in the embedded VSCode. You can edit them yourself.
Before anything touches your servers, the AI runs `pyinfra --check` in the isolated session container, against the real targets. The diff streams to your browser. No changes applied. Every dry-run is persisted with stdout, stderr, and result, tied to the commit SHA.
You click Propose. A different teammate with read-write access reviews the diff, the dry-run output, the code in git. They approve. The apply runs in the same isolated session container, logs stream live, the full result lands in an immutable audit trail. SSH key is decrypted in memory, written to tmpfs, shredded on exit.
Your data stays on your network. The AI stays on a leash.
Fleet data, code, and audit NEVER leave.
Only inference calls. No data stored.
Coding model runs on-premises via llama.cpp. Nothing leaves the network. Zero external dependencies. Release 2 fine-tunes the model with DPO on real production feedback captured from day one.
"Non inultus premor" — Motto of Nancy, Lorraine, since 1477.
We do not wrap PyInfra, we shape it. Direct influence on the fact/operation API roadmap. This is not a "we use open source" story. This is a "we ARE the open source" story.
Jinn, our predecessor, serves paying enterprise clients in the Gulf: government, fintech, healthcare. 500+ servers managed. We know the buyer, the deployment, and the objections. We are not building from scratch.
Cloud AI tools opened the market. But banks, hospitals, and government cannot use them. Their data cannot leave their network. We serve the customers they cannot.
The AI writes PyInfra code, not bash. It can dry-run freely. It has no `apply` tool. Apply requires a human proposal followed by a different human's approval. The gate is in the code, not just the policy. No prompt injection path to execute.
Every line of code that ever ran on your fleet has a commit SHA. Every change has a diff. `git log` is auditable, `git show <sha>` is reproducible. PocketBase carries the things git is bad at: logs, results, feedback.
Every install captures approve / reject / edit / rollback feedback on every apply. Release 2 fine-tunes a coding model with DPO on that real preference data, served on-prem via llama.cpp. Every install we ship makes the next install's model better.
Energy, transport, water, defense primes. Air-gapped networks, zero external dependencies, LPM obligations. ANSSI in the room.
Large enterprises freshly pulled under NIS2: manufacturing, postal, digital infrastructure, food. New audit mandates, understaffed IT.
Ministries, hospital GHTs, metropoles, territorial authorities. Sovereignty-first, HDS, SecNumCloud readiness. Chronic hiring gap.
Banking, insurance, healthcare groups, energy, telecom. DORA, ISO 27001, change control. Auditors live in the room.
Founder
Built Jinn, the predecessor serving enterprise clients in the Gulf: government, fintech, healthcare. 500+ servers managed.
HQ
Nancy, Lorraine, France
Born in the city of the thistle.
See Inultus patch, harden, and report on a live fleet in 15 minutes.
Schedule a democontact@inultus.com