GenAI Studio
A pilot-to-production programme. build a lean MVP or embed AI into
a live workflow, then scale with governance.
Google Cloud
Verified Expertise
As a leading Generative AI company, we hold Google Cloud specialisations in both Generative AI Services and Cloud Infrastructure, recognising our independently assessed expertise and proven track record of delivering innovative solutions that drive measurable client success.
What is
GenAI Studio?
Your gateway to AI development services. GenAI Studio helps teams improve the efficiency of existing workflows or pilot new ideas, features or MVPs quickly. Using our comprehensive library of pre-built agents, patterns and components, we help you build fast, without compromising security and governance.
01
Pilot an idea,
feature MVP
For when you want to test a fresh idea quickly. You get a brief, a clickable prototype, a working demo and clear next steps.
02
Embed AI into an
existing workflow
For when you need measurable impact in a live workflow. You get a governed pilot in your tools, a simple performance dashboard and a production plan.
Our Unique Proposition
One integrated pod, zero handoffs, and weekly progress accelerated by our proven AI playbook. Underpinned by our AI consulting services, we ensure your roadmap is practical, secure, and aligned with measurable outcomes.
Ships in weeks, not quarters
Work to a 12 - 16 week schedule with named outputs including brief, flows, designs and a working prototype ready to show.
The more thought-out the process, the stronger the outcome
Governance by design
Access controls, audit logs and a clear go/no-go before anything goes live.
Built for your stack
We work with your cloud, models and tools so approvals move faster.
From prototype to production
Every engagement ends with a production plan, support targets and a safe rollback.
Our Operating Model
A simple, four-step path from idea to impact. Aligned to your KPIs, delivered by a dedicated pod, and governed at every stage, strengthened by our expertise in AI software development to move seamlessly from pilot to production.
1
Intake & Prioritise
We start by meeting your stakeholders to align on goals, success measures and guardrails. Together we assess digital maturity, data and security constraints, then size value and feasibility to pick the first use case.
You leave this phase with a short, prioritised plan, baseline metrics and a one-page brief for the initial prototype.
2
Prototype Sprint
A single cross-functional pod (Product, AI/ML, Engineering and DevOps) moves from brief to working prototype on your stack. As an AI services company, we provision the lab (cloud environments, models and data pipelines), run weekly sprints with show-and-tells, and make progress visible.
By the end, you have a working prototype, a clickable experience and a simple test plan with results, built with the right access controls and audit logs in place.
3
Review & Enable
We review outcomes against the baseline and decide to productionise, pause or iterate. This includes security and compliance checks, light training and change-management prep.
You receive a concise decision pack and a production plan covering targets, monitoring and support.
4
Embed & Scale
We ready the solution for production, enable monitoring, and phase the rollout. Your team receives runbooks, service targets, escalation paths, and training. Then we either hand over, expand, or refocus the pod on the next priority.