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Practice

Forward deployed engineering for AI-native work.

We embed small senior teams with your operators and engineers. The work runs on an AI-native SDLC: automation-heavy, evaluated continuously, and designed for the controls regulated teams need.

How we work

Our teams are deliberately small and senior. We move quickly because the work is supported by reusable artefacts: evaluation harnesses, agent patterns, integration scaffolds, security controls, delivery playbooks, and automation that removes repeated effort.

  • 01

    Forward deployed

    We work inside your context, with your people, systems, data, and constraints. The work is shaped by the operating reality, not a remote backlog.

  • 02

    AI-native SDLC

    We use AI across discovery, design, coding, testing, documentation, evaluation, and release. The process changes, not just the tools.

  • 03

    Automation by default

    If a task repeats, we try to automate it. That applies to customer workflows, internal operations, QA, reporting, deployment, and delivery itself.

  • 04

    Built for regulated use

    We have built complex AI use cases in environments where auditability, security, data boundaries, and human oversight matter from day one.

  • 05

    Highly leveraged teams

    Top-quartile engineering talent, working with strong artefacts and automation, can solve in days what larger teams can turn into months.

  • 06

    Capability transfer

    Your team works alongside us. The code, patterns, evaluation assets, and operating knowledge stay with you.

The shortest distance between an AI idea and an AI outcome is one engineer in the room.

Popularised by Palantir, refined by Anthropic & OpenAI, productised by Semanti.
Build with us

Have something complex that needs building?

Tell us the workflow, system, or AI use case you need to move. We will tell you how we would structure the team, what we would automate, and how we would prove it works.

Talk to an engineer