Questions security teams ask.

Every project lives in a private repository your organisation owns. While an agent works on a task, the code it needs is sent to the AI model provider that runs the agent, under business terms that don't allow training on your data. We name those providers and their data-retention terms during scoping, before any code is shared, and can work within your approved-vendor list.

Risk decides. Routine changes that pass every independent layer can merge automatically; anything touching security, money, data, infrastructure or the agents themselves always goes to a human with the evidence laid out. Your organisation sets where that line sits.

No. Agents work in disposable, isolated environments with no credentials, no secrets and an allowlisted network path. They can't merge or deploy anything themselves.

Yes, both in systems we build and ones you already run: retrieval over your documents, classification and extraction, drafting, and agents that act through tightly scoped tools. We're model-agnostic, work within your approved-vendor list and data-retention requirements, run on accounts your organisation owns, and ship each feature with evaluations, logging and human review for high-risk outputs.

Yes. We deploy where you need, behind your single sign-on, with logs that feed your existing monitoring.

You keep everything: code, history, documentation, runbooks and the record of every change. Any capable engineering team can take over.

No, and banning them usually just pushes them out of sight. We inventory them, review them, harden a copy while teams keep working, and give each one an owner and a record of every change.

Yes. Many AI-built tools are written by operations, finance or sales staff with an AI assistant, and that's fine. What matters is what the tool touches, not who wrote it.

Agents do the implementation work inside a system that verifies every change, so a small team delivers what used to need a large one. That's how we come in at a fraction of the cost and time, with a fixed quote after scoping.

No. The speed comes from agents doing implementation, not from skipping review. Every change passes layered, independent checks, and anything touching security, money, data or infrastructure goes to a human.

Yes. AI advisory is a standalone engagement: use-case prioritisation, tool selection, governance and rollout. If a use case needs custom software, that's scoped and quoted separately. How AI advisory works.

Yes. Network infrastructure is where Tethered started, and it remains a core service.