Understand and design
Agree the business outcome, process boundary, users and baseline. Design the architecture, interfaces, data flow and access model.
Services / AI & automation delivery
From business requirement
to working AI and automation.
We take business needs through solution design, engineering and integration, with the controls, testing and adoption needed to put the solution to work.
Discuss your delivery requirementsDelivery around your business
Start with the outcome. Design for the environment.
A focused process improvement or a wider implementation, with scope and responsibilities agreed from the outset.
We assess your existing platforms, data and cloud environment before recommending an architecture. Integration, access, running costs and the people who will operate the solution are part of that decision.
Our team combines business consulting with solution architecture, data and AI engineering. We agree the acceptance measures and client dependencies before committing to delivery.
An engagement with clear decisions
What happens between the brief and handover?
Engineer and integrate
Build the agreed capability and connect it to the relevant systems. Put exception handling, human review and security controls into the workflow.
Test and validate
Use representative inputs, failure cases and user acceptance tests. Assess output quality, performance and costs against agreed criteria.
Embed and hand over
Prepare documentation, training, monitoring and operational ownership. Agree release approval and support before go-live.
Delivery evidence
See the consulting and engineering together.
UK retail finance automation
Process redesign, Power Platform engineering, integration, audit and exception controls, training, documentation and hypercare. Five production-ready automations with documented integration and controls.
Read the delivery storyConversational retail data
An Azure MVP translated natural-language questions into SQL and traceable outputs. A separate proof of value explored CRM data. These are distinct early-stage engagements.
See the MVP and proof of valueWho takes responsibility
Business leadership and technical accountability.
Engagement lead
Owns the agreed business scope, client relationship and delivery coordination. Keeps decisions and dependencies visible.
Architecture and engineering
Technical leadership directs solution design and review; engineers build and test the capability. The role mix follows the agreed scope.
Your business and technology owners
Provide access and process expertise, validate benefits and accept the solution. Operating responsibilities and release decisions are agreed together.
Technical assurance is led by Jay Wyke, AI Architect. Constanza Bustamante, Senior Delivery & Operations Manager, brings delivery planning, operational coordination and commercial governance. The team and responsibilities are agreed around each engagement.
Meet the foundersFrom implementation to improvement
Make the next stage a deliberate decision.
A proof of value tests a specific feasibility or value question. An MVP delivers a limited working capability; a pilot tests it with users. Production use follows the agreed acceptance, ownership and release decisions.
We review what the work has established before proposing the next stage. An ongoing AI Value Partnership can support a wider roadmap; live operational support is agreed separately.
Talk to Ignite
Have a requirement, brief or prototype?
In 30 minutes, we’ll discuss the outcome, fit, dependencies and evidence needed to scope the next stage.
