Success Story

Transforming Invoice
Processing with AI:
Landsec’s Journey
to Faster, More
Accurate Operations

98.6%

Cost Reduction per month
79.2%

Efficiency gain cutting the average AP invoice backlog from 1,200 to 250
100%

Supplier name accuracy achieved, with errors fully eliminated

The Overview

 Landsec is one of the UK’s leading real estate companies, focused on building and managing high-quality destinations with true scarcity value. Landsec have been partnered with Godel for over five years, initially to help scale team capacity and support ambitious goals. Today, the partnership continues to evolve, with Godel helping Landsec modernise its development and invoice processing capabilities.

The Challenge

As Landsec worked with a growing portfolio of organisations and demand continued to accelerate, they recognised the need to bolster their in-house development capability to maintain the required scale and speed of delivery. At the same time, Landsec was pursuing an aggressive cloud-first strategy, with Azure as its preferred platform. With multiple applications identified for deployment, the organisation faced a clear capacity gap that prevented it from progressing its cloud migration at the speed the business demanded.

The Solution

Their primary objective was to rapidly expand delivery capacity by outsourcing development, enabling the use of AI to transform invoice processing and support a shift toward faster, more accurate operations. By leveraging Godel’s expertise and deep AI knowledge, Landsec was able to scale its development capacity, modernise its Azure-based technology estate, and transform invoice processing through an AI-driven solution that significantly reduced costs and backlogs while improving accuracy, operational efficiency, and internal customer satisfaction.

Scalable Development Capacity

Nearshore teams enabled rapid scaling without increasing permanent headcount.
Azure Cloud Enablement

Provided Azure experienced engineers to accelerate application deployment and reduce delivery risk.
Modern Front End Development Capability

Angular-skilled teams aligned to Landsec’s technology stack enabled consistent, modern development.
Cross‑Managed, Embedded Delivery Model

Operated as an embedded, cross‑managed team, working as an extension of Landsec’s internal function.
AI‑Driven Invoice Processing Solution

Supported adoption of an Azure OpenAI‑based approach, improving accuracy, flexibility, and cost efficiency.
Reduced Invoice Backlogs and Operational Pressure

AI‑driven processing reduced invoice backlogs by an order of magnitude.

"When we decided to embrace AI across the company, with Godel we explored different ways to integrate Copilot into our operations ensuring we leveraged AI responsibly and effectively, and after our first experiments, we were genuinely impressed by its accuracy. As we continued, it became clear that Copilot offered far greater control, ease of use, and cost savings. Over the past three months, we've seen substantial improvements in accuracy, speed, and overall performance."

Chris Wilkinson | Solutions Architect at Landsec

Accelerated adoption of Microsoft Azure

With Godel’s support, Landsec successfully deployed applications to Microsoft Azure, overcoming internal skill and capacity constraints at a critical point in its cloud transition.
Improved accuracy and effectiveness of invoice processing

By adopting an Azure OpenAI-based approach, Landsec achieved significantly higher accuracy compared to earlier solutions.
Dramatic reduction in AI processing costs

The new solution delivered an approximately 99% reduction in costs, while also improving output quality and control.
Substantial reduction in invoice backlogs

The number of invoices awaiting processing decreased by an order of magnitude, allowing backlogs to be cleared faster and more consistently.
Sustained Delivery Confidence

Smoother operations and reduced backlogs improved day-to-day experience and internal satisfaction, while a stable Godel team preserved institutional knowledge, maintaining delivery momentum and confidence across phases.

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