AI & Software
Engineering
We build software the way a security team wishes everyone would: small blast radius, real observability, secrets where they belong. And we build AI systems that are measured rather than demonstrated.
Product engineering
Embedded squads or a full delivery team for a product you need in market. Discovery, architecture, build, release — with your name on the roadmap and ours on the pager.
Platform & cloud
Infrastructure as code, CI/CD, environment strategy, observability and cost control. The unglamorous layer that decides whether your team ships weekly or quarterly.
Agentic AI & LLM systems
Retrieval, tool use, evaluation harnesses, human-in-the-loop controls and guardrails. We built AithSense this way, so the failure modes are not a surprise to us.
Data platforms
Pipelines, warehousing and the access model around them. Useful data without quietly building your next breach out of copies of production.
Secure SDLC enablement
Threat modelling in design review, scanning developers do not route around, dependency and secrets hygiene, and training your engineers actually attend.
Modernisation & rescue
Inherited a system nobody wants to touch. We map it, stabilise it, carve it into parts that can be changed safely, and leave documentation behind.
An AI Project
Is a Security Project.
New data flows, new identities, new ways to leak. We treat those as first-order design constraints, not something to review after launch.
A test set and a measurable target before the demo becomes a dependency. If the numbers do not hold, we tell you rather than tuning the prompt until the slide looks good.
Input and output validation, tool permissions, rate limits and a human in the loop where the blast radius warrants one. An agent with write access is a privileged account.
Where each answer came from, what the model was allowed to see, and how to prove it later. Retrieval you can defend to a regulator, not just demo to a board.
Budgets and p95 targets set up front. A system that is correct but too slow or too expensive to run is a system you will quietly turn off.
Engineering, answered.
How is this different from a normal software agency?
We are a security company that also builds software, so the security assumptions come baked in: small blast radius, real observability, secrets where they belong, and threat modelling inside design review rather than after launch. The team that knows how systems get attacked is the team writing yours.
We want to ship an AI or LLM feature — where do you start?
With a test set and a measurable target before the demo becomes a dependency. We build the evaluation harness, the guardrails, the tool permissions and the human-in-the-loop controls, and if the numbers do not hold we tell you rather than tuning the prompt until the slide looks good. We built AithSense this way, so the failure modes are not a surprise to us.
How do you engage — a full team or embedded people?
Either. We provide embedded squads that sit inside your existing team, or a full delivery team that owns a product end to end — discovery, architecture, build and release. Every engagement is scoped to what you actually need rather than a fixed package.
Can you take on a system nobody wants to touch?
That is our modernisation and rescue work. We map the thing, stabilise it, carve it into parts that can be changed safely, and leave documentation behind so the next change does not need us. You get back a system your team can move in again.
How do you stop an AI system becoming slow or expensive to run?
Cost and latency are treated as features, with budgets and p95 targets set up front. A system that is correct but too slow or too costly is one you will quietly turn off, so we design against that from the start — alongside data lineage you can actually audit later.
Find Out What an Attacker
Would Find First.
A forty-five minute review with a senior engineer. No slides, no obligation, three concrete actions at the end.