A team that ships every sprint.
A cross-functional pod that turns your automation pipeline into production bots on a steady cadence. You set priorities. The pod owns delivery.
Outcomes from a team, not hours from people.
A pod is a stable team that works through your automation pipeline in sprints. It includes the roles needed to go from process assessment to hypercare, so work does not stall waiting for an analyst or a tester.
The pod reports on throughput, quality and benefits. It follows your CoE standards or brings ours. Because the team stays together, it builds deep knowledge of your systems, which makes each automation faster than the last.
Assessment, design, build, test, deployment and hypercare inside one team.
Sprint planning gives you a clear view of what ships next.
Reusable components and system know-how build up over time.
Pod composition and practices.
Pod lead
Owns sprint planning, stakeholder communication, risk and reporting, and reviews every design.
01Business analyst
Runs process walkthroughs, writes PDDs and acceptance criteria, and confirms benefit estimates with process owners.
02Automation developers
Build on your chosen platform using shared libraries, config-driven design and peer code reviews.
03QA engineer
Writes test cases, prepares test data, runs regression and supports UAT with business users.
04Architect on call
A senior architect reviews solution designs, infrastructure choices and AI components each sprint.
05Governance pack
Sprint reports, a benefits register, a risk log and a monthly steering review with your sponsor.
06From pipeline to production.
Mobilise
We agree pod size, platform, standards and access, and onboard the team in your environments.
Prioritise the pipeline
Together we score candidate processes on value, complexity and readiness, and fill the first sprints.
Deliver in sprints
Two-week sprints move each automation through design, build, test and UAT, with a demo at the end of each.
Deploy and stabilise
Releases follow your change process. Hypercare covers the first weeks of production for each bot.
Review and scale
Monthly steering reviews look at throughput and benefits, and decide whether to scale the pod up or down.
How we keep the pod accountable.
- Throughput tracked as automations delivered and story points completed per sprint
- Quality tracked through defect leakage into UAT and production
- Benefits register updated as each bot reaches steady state
- Every solution design reviewed by an architect before build
- Code reviews and a shared component library on every change
- Pod size adjusted at sprint boundaries with agreed notice
- Specialist roles such as AI engineers added for specific sprints
- Full documentation and handover pack if you take the work in-house
How big is a typical pod?
Most pods have four to six people. We size them to your pipeline and adjust as demand changes.
How is a pod different from staff augmentation?
Augmented specialists work under your direction. A pod owns delivery of agreed outcomes and manages its own work within your governance.
Can a pod work across more than one platform?
Yes. Many clients run, for example, UiPath for complex processes and Power Automate for departmental flows. We staff the pod accordingly.
What happens to the work if we end the engagement?
You own everything built. We provide source, documentation and a structured handover to your team or another provider.
Can a pod also support bots in production?
Yes, it can take on support, though larger estates are often better served by a separate managed automation service.
Find your first ten automations in two weeks.
A structured discovery sprint that maps your processes, scores them for automation potential and hands you a prioritised roadmap with effort and payback for each.