intelligent Engineering

Welcome to the new era of AI-augmented software delivery.

Improving developer productivity and software quality while codifying culture for future growth.

Learn how we helped Talon modernise a legacy system with GenAI, achieving a 40% velocity boost

See how intelligent Engineering works in practice

Introducing intelligent Engineering

Move beyond the ‘Copilot’ pilot. AI tools are everywhere, but they aren’t fixing delivery challenges alone. To get real value, courageous leaders need to wire AI workflows into their entire Software Development Life Cycle (SDLC), not just their integrated development environment.

While these leaders believe in AI’s ability to drive higher productivity per engineer; to codify their culture and to deliver higher quality software, they are looking for new partners with fresh ideas who can support safe adoption and drive measurable gains. intelligent Engineering is built for them; a practical approach to AI-augmented software delivery across the SDLC.

Many teams have adopted AI tools but haven’t seen the promised benefits, yet. The challenge isn’t generating code; it’s unifying standards and culture with new AI workflows.

AI for Software Engineering, Not(only) Code Generation

Greg Reiser, Head of Client Partnerships, North America

intelligent Engineering solves these challenges by blending human expertise with the power of AI.

Using our proven frameworks and experience we capture and then encode your context, patterns, tools and standards into our custom AI layer. We design and implement agentic workflows for planning, specs, architecture, coding, testing, release and operations, then govern them with organisational prompt libraries, templates and patterns your teams own.

Unlike ‘black box AI’ and tool-only pilots, intelligent Engineering combines transparency, guardrails, proof-of-value and measurement to safely embed AI into an operating model your squads can sustain.

Principles of intelligent Engineering

As part of our commitment to using AI responsibly, we have established five principles that govern how we safely and effectively work with AI:

AI auguments; humans stay accountable

The responsibility for outcomes always rests with those who use the AI, not the AI itself. You cannot delegate responsibility.

Context is everything

The quality of AI outputs depends on the clarity and the richness of human input.

Smarter AI needs smarter guardrails

The more we rely on AI to generate code or ideas, the stronger our review and validation habits must become.

Shape AI deliberately

Choose when and how to use AI. Don’t let the tools define your process or culture.

Learning never stops

AI and its best uses change constantly. Teams must evolve their practices through steady experimentation and reflection.

Principles of intelligent Engineering

Karun Japhet, Solution Consultant, India

How intelligent Engineering Works

Shaping AI

The intelligent Engineering framework begins with Shaping AI: we map agentic workflows, codify standards into prompts/templates, and connect tools to your stack.

Leading AI

We then start Leading with AI - delivery in a joint squad, applying practices like specs-before-implementation, test-driven mindset, and human review across the SDLC.

Measure & Mature

Finally, we Measure & Mature - tracking uplift, closing gaps and productising what works so other teams can adopt it with confidence.

Realising Efficiency and Productivity through intelligent Engineering

Leveraging the intelligent Engineering framework, demystify how AI drives productivity and efficiency gains across the SDLC to solve real-world problems

The benefits of intelligent Engineering

More productivity

Increased productivity per engineer: raising output without headcount.

Cultural Codification

Codification of your culture: your beliefs and behaviors reinforced through the tools you use everyday.

Zero lock-in

Zero lock-in by design: we prioritize reversibility and portability, ensuring you own your prompts, patterns and context.

Clients using intelligent Engineering

Delivering a 40% Velocity Boost in the Modernization of Talon Plato's Legacy System with GenAI

Sahaj Software modernized Talon's Media Owner Portal from legacy Angular 17 to a contemporary React architecture. This initiative went beyond a simple rewrite, piloting "intelligent Engineering", an AI-augmented, Gen-AI-powered workflow. This approach effectively managed evolving UX needs and technical debt, ensuring predictable delivery and establishing a scalable modernization blueprint, which positions Talon as a digital innovation leader in the OOH space.Talon is a specialist Out-of-Home (OOH) agency with over 30% UK market share and operations in the UK, USA, Canada,...

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Project xEMR: Building an AI-Powered EMR System with Agentic AI Workflows

Project xEMR demonstrates the successful use of advanced, automated AI systems to build a complex medical records platform that strictly adheres to all healthcare regulations. The intelligent Engineering (iE) approach fundamentally transformed the software development lifecycle by having AI agents handle 90% of the work, resulting in a 300% increase in engineer productivity.October 2025The healthcare industry is bogged down with complex, time-consuming paperwork and tasks, and often the standard Electronic Medical Records (EMR) systems are part of the problem. That's...

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