Software Delivery Conversion with Endava’s AI Agents

solved complex business problems with technology for 25 years HomeIt reached a milestone in March 2026. When the company received Codex and ChatGPT Enterprise from the center of the organization, the software delivery was no longer installed on code writing. Analysis, design and construction phases have become a combined flow, rather than a cycle that lasts weeks before. And this change was not only the speed issue for a company waiting for the review of the code that reaches the million rows.

Endava’s Agentic Organization Structure

Endava now defines itself as agentic organization (agentic organization): a structure that senior-level judicial encoded AI agents work side by human teams at every stage from the project to delivery. This definition is quite specific in the industry.

"We’ve previously written many code ourselves. Now we review the work done by Codex"The regional CTO of Endava Mr.mr.He tells you about this slip. The time distribution of engineers also validates this: code writing tasks dropped to 25% from work that last 60% a day, architecture and system design rise from 15% to 55%.

To say in another way: developers do not write any code, but doing more valuable things.

CaseFlow: AI-Native Methodology

Software companies often add AI to existing jobs. Endava made the opposite. CaseFlowEndava’s AI-native engagement lifecycle: it’s a method that connects every change towards production from the idea and organizations to achieve faster, secure and responsible change in AI era.

This is a methodology working in four AI-enhanced phase: Signal, Explore, Govern and Evolve. The structure emphasizes setting the context correctly before moving the AI agents into the code. Before writing a AI agent code, business difficulty, competition context and desired results are clearly understood.

CaseFlow is designed for internal use in the first place. But success has become no need. When used in sectors ranging from financial services to mobility, CaseFlow often reduces the opening time to 40%, telemetry and traceability increase trust with each version.

Error: Requirements Darboğat

Endava’s law team brought a complex problem to the development team: thousands of page contracts review against certain criteria. Earlier, the description of what the lawyers will be built received weeks. Instead, the team recorded a two-hour deep diving meeting, transferring the text to Codex and produced a working requirement token.

Here is important: this is not only "faster". Endava no longer evaluates analysis, design and construction as sorted stages. If each of these before is taking days or weeks, now Codex is able to pack them as a single combined tool.

Codex: Not Code Assistant, Desktop Agent

There is a misunderstanding about Codex: "A version of the Copilot". Not. The biggest profit of Endava came from using Codex as desktop agent, not as code writing assistant. Besides the code, the profit was understood when it applies to the requirements, design, customer communication and operations.

Codex is also used for jobs around the code: writing documents, creating updates, analyzing data. When you look at the source, this is not a code editor, the workflow platform.

Corporate Security and Management

GartnerHe called OpenAI as a leader in corporate coding agents in 2026; due to the powers of Codex’s agentic software development, corporate governance and sandbox execution. Sandbox is critical for businesses: it means to emit production code with giant environment.

Codex approval doors, role-based access control (RBAC)The operating system level includes sandbox and auditable workspace logs - controls that they need before deploying AI on industries such as banking and insurance.

This explains the reason for Endava to do software for banks and insuranceers. A large number of agents that are not connected with governance fail. Endava buried governance into methodology.

Code of Senior Information

A strange concept for many non-technical company: encode the master architect. But the essence of the structure of this Endava.

Sonava’s Global SVP of Agentic Architecture, Mike Krolnik, who filled the gap between the senior and junior engineers of Codex and turned into information that complex requirements are accessed to the junior members, which was considering that non-experienced developers are highlighted in the description of the Senior Supervision.

Think in another way: the senior architect in the growing company can not be available when it started every new project. But decisions and architect principles given to Codex remain fixed. Agents apply the cover information of the senior to new codes.

97% more pull requests more combined team reports - along with the corrected workflow, code review time has increased, making review new bottleneck. This can be a second-liquid problem but practical: beyond CI/CD, the software needs real human attention.

Corporate Myseme: Fast Kanaat

Endava announced a strategic agreement to distribute ChatGPT Enterprise license with OpenAI to more than 11,000 global employees. This substance is not: no employee in the Endava left outside.

A pilot team named ChatGPT Champions tested to integrate technology for several months and set up best practice. Then the company pulls an informed roll in the diameter. Endava launched a mandatory AI training module to maximize the power of AI and ensure responsible use.

This is critical: other companies distribute AI tools and compile "free use". Endava created a methodology, then centered.

Large Economic Probe

AI Agent The market was $7.6 billion in 2025 and predicted by 49.6% annual growth in 2033. Endava’s movement is not only related to software speed: the signal that corporates have to re-configurate company operations models.

Endava decided: the code will enter the task of writing, the context and design. Endava engineers now review that they produce very Codex from the code writer. The fee structure came with it. Preparation and review is more valuable.

Being the "agentic organization" in other words of Endava, not only a marketing statement. A real transactional shift.

Frequently Asked Questions

What does Endava distinguish Codex from ChatGPT?

Codex Enterprise contains distributed control, visibility and governance across mature codebases and production flows. Teams also use code for jobs around: writing documents, creating updates, analyzing data. ChatGPT is more general; Codex flow-native.

Is it easy to introduce CaseFlow?

CaseFlow has many organizations experience AI in insulated use-cases after taking embedding. Enablement programs keep teams confidently working with agentic tooling, policy-in-pipeline controls governance from consis. In other way: methodology contains distribution and training.

How much time does it save?

Endava accelerated software delivery using Codex to requirements analysis weeks. But this company-custom figure. Similar teams should wait 30%-40%; Endava’s senior knowledge can be 60%+ as coded.

Is Codex safe?

Codex Enterprise is adopted with privacy, admin control, ARM protections and auditability. OS-level sandboxing on macOS and Windows allows developers to safely work hunger agent activity limited retention. There is no training on enterprise data on default and the data is encrypted on transit and rest.

Can small companies use CaseFlow?

CaseFlow itself contains principles that can be applied for everyone: context first, then proxies. However, the version of Endava is built on 11,000+ staff. Smaller teams can make similar principles (gereksinim formatting, agent setup, review); methodology scale.

Does AI agents change software engineers labors?

GPT-5.2-Codex answered a hybrid future to this discussion: artificial intelligence did not replace software engineers, but they transformed what work will do in them. Endava evidence: engineers write less typical code, making more design and review.

Matthew Cloke used a simple metaphor as CTO:

"If I don't have an agent working in the background, I think I'm spending my time. "

This was just more than one vehicle. This was a business philosophy.

Rename your thought about software delivery, redefined your team’s job – these precision works. Endava tried to do this with its agentic organization structure. The result was not clear in mechanical engineering, but it was explained in business findings: less sentence texts, more output, less than junior restriction. Or the most essence: the seniors architect returned to the side of the actual problem.