You have ambitious digital or AI goals but no clear delivery roadmap
You see opportunities across teaching, student services, and operations, but need help turning ideas into a prioritised, realistic plan.
Education & EdTech
Modern engineering and AI delivery for education
- Product and platform teams that understand complex academic and regulatory environments
- From discovery and pilots to production-grade systems and ongoing optimisation
- Flexible engagement: fixed-scope initiatives or embedded delivery pods
When our education and EdTech support is a strong fit
We’re most effective when there is strategic intent to modernise, and a need to move from fragmented initiatives to an executable plan.
Your internal teams are stretched on capacity or specific skills
Product, data, and engineering teams are at bandwidth or lack experience with AI, modern cloud architectures, or complex education integrations.
You’re under pressure to improve retention and student experience
Leadership is focused on measurable gains in engagement, completion, or satisfaction and needs technology initiatives that clearly support those targets.
Legacy systems slow down new initiatives
Existing SIS, LMS, or finance platforms make it hard to launch new services or integrate AI, and you need pragmatic ways to modernise without a risky rewrite.
You need to balance innovation with compliance and safeguarding
You want to use data and AI responsibly, with clear governance around privacy, academic integrity, and student safety.
You want predictable delivery, not endless experimentation
You’ve run pilots or proofs of concept and now need disciplined execution—fixed-scope projects or embedded teams that ship and scale in production.
Example use cases
Where we’re helping education leaders today
How we work
A delivery approach built for education and EdTech
We combine domain-aware discovery with disciplined engineering so you can move from idea to production without compromising compliance, pedagogy, or reliability.
01
Clarify objectives and constraints
Align with academic, commercial, and regulatory stakeholders on the outcomes you need, success metrics, and guardrails around data, ethics, and safeguarding.
02
Prioritise and shape initiatives
Assess opportunities across learner experience, staff productivity, and operations, then prioritise a realistic roadmap based on impact, feasibility, and change readiness.
03
Design and validate solutions
Prototype user journeys, data flows, and AI components; validate with educators, students, and operations teams to de-risk before full build.
04
Build, integrate, and harden
Deliver production-grade systems—either as fixed-scope projects or embedded pods—covering integrations with SIS/LMS, identity, payments, and analytics.
05
Roll out, train, and iterate
Plan phased rollout, support training and change management for faculty and staff, and use real-world usage data to refine models, rules, and workflows.
Business Outcomes
- Clear, sequenced roadmap tied to learner and institutional KPIs.
- Faster path from pilot to production with reduced delivery risk.
- Modern, scalable platforms that integrate cleanly with existing systems.
- Improved student outcomes, retention, and staff productivity.
- Governed, compliant use of data and AI across your estate.
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