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Process

Pilot. Build.
Scale.

A simple loop that keeps control and pace in balance.

Lifecycle

Four phases that never skip the essentials.

Every engagement flows through discover, design, build, and scale loops so teams stay aligned.

01

Discover & align

Identify friction, data sources, and stakeholders.

02

Design control layers

Define guardrails, approvals, and measurement before code starts.

03

Build & integrate

Ship the agent, product, or connector with continuous feedback.

04

Scale & enable

Roll out, train teams, and hand off operations.

Next step

Invite us to your discovery workshop.

Book 45-minute session
Operations

Keeping agents reliable once they launch.

We stay close to your teams with observability, guardrails, iteration rituals, and support.

Observability & insight

Understand everything agents do with rich telemetry.

Safety & guardrails

Guard critical actions with approvals, policies, and isolation.

Iteration rituals

Weekly loops keep the roadmap fresh and aligned.

Support & enablement

We stand behind launches with training and on-call options.

Dockerised agents in plain language

A simple model: an AI worker lives in a container, gets the keys you approve, and reports everything it does.

Agents run in clean containers

Each AI agent ships as a Docker image with its own tools, prompts, and guardrails.

Access stays scoped

We control credentials, file access, and network reach so the agent only touches what it needs.

Connect to your stack

Agents call your CRM, ERP, or APIs through vetted connectors you approve.

Humans stay in the loop

Important actions can pause for sign-off. Every step is logged for easy review.

Scale gradually

Start with one workflow, then add more agents as confidence and ROI grow.

Deploy where you want

Run agents on your cloud or on-premise infrastructure—your data never leaves your perimeter.

Under the hood we lean on containers, scoped API keys, detailed logging, and observability so agents stay helpful and compliant.

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