13X FASTER DELIVERY OF AN AI-POWERED PRODUCT FOR A LEADING LEGAL TECHNOLOGY COMPANY

By adopting the agentic delivery model, projected effort dropped from 1,107 hours to 88 hours, delivery costs were reduced by 7.5x, and development and QA execution accelerated by 13x.

INTRODUCTION

Some of the most promising ideas never reach the market—not because they lack business value, but because the cost, effort, and time required to deliver them outweigh the expected return.

A leading legal technology company faced this challenge with a strategic AI-powered product initiative. While the concept had already been defined and validated, the projected delivery effort made it difficult to prioritize, leaving the initiative on hold despite its potential business impact.

At the same time, the organization was pursuing a broader vision: becoming an AI-native product company capable of accelerating innovation through intelligent automation and modern engineering practices.

To explore a different path forward, the organization partnered with CI&T to rethink how products could be delivered. Leveraging Powered by CI&T Flow and an agentic delivery framework, the teams transformed a previously dormant initiative into a production-ready solution in a matter of weeks.

The result was a new delivery model that reduced implementation effort by more than 90%, accelerated delivery by 13x, and demonstrated how AI can fundamentally change the economics of software innovation.

THE CHALLENGE: BUILDING AN AI-NATIVE DELIVERY MODEL

Beyond delivering a single product, the organization sought to establish a repeatable approach to AI-driven software development that could accelerate future innovation initiatives.

High Cost of Innovation

A strategic AI initiative had already been defined and designed, but the projected effort and delivery costs made execution difficult to prioritize.

Complex Technology Landscape

The organization operated within a technology ecosystem that combined modern capabilities with legacy components, creating additional complexity for software delivery.

Establishing an AI-Native Engineering Model

As a growing product organization, the company wanted to move beyond isolated AI use cases and adopt a repeatable model for AI-driven software development.

THE SOLUTION

CI&T implemented an agentic software delivery approach designed to accelerate both upstream and downstream activities across the development lifecycle.

Faster Solution Definition

AI-powered workflows supported solution definition, requirements analysis, and prototyping activities, reducing the time needed to move from concept to implementation-ready plans.

Agentic Development Pipeline

A customized downstream pipeline automated key engineering activities, including:

• Architecture design
• Technical solution generation
• Software development
• Testing activities
• Infrastructure deployment scripting

This enabled teams to execute work much faster while maintaining human validation at critical checkpoints.

AI-Driven Delivery Framework

The initiative served as a practical validation of an AI-native software development life cycle (SDLC) model, demonstrating how intelligent agents could collaborate across multiple stages of software delivery.

THE IMPACT

The results demonstrated the potential of agentic software delivery to fundamentally change how organizations approach product development.

SIGNIFICANT TIME REDUCTION

The original delivery
estimate projected:

Using the agentic delivery framework, the
work was completed with:

1,107

hours of effort

88

hours of human effort

FASTER DELIVERY

13x

than the traditional delivery estimate

LOWER COSTS

7.5x

reduction in delivery costs

ACCELERATED TIME-TO-MARKET

An initiative that had remained inactive due to cost considerations was
transformed into a working Minimum Viable Product (MVP) within weeks.

TECHNOLOGIES USED

CI&T FLOW

CI&T Flow Enterprise AI Management System that accelerates software delivery by integrating intelligent agents into engineering workflows.

AGENTIC SDLC FRAMEWORK

A delivery model that combines AI agents and human expertise across solution definition, development, testing, and deployment activities.

AI-ASSISTED DEVELOPMENT

Intelligent automation supporting architecture design, coding, testing, and deployment preparation while maintaining human oversight throughout the process.