Transforming Legal Operations with AI: Aderant’s Journey to Enhanced Efficiency
Guest Contributions by Angela Mapes and Adam Walker of Aderant
The Challenge: Information Scattered Across Six Systems
The Solution: AI-Powered Search and Workflow Automation
Real-World Impact: Resolving Critical Infrastructure Issues
Quantifiable Results: Significant Efficiency Gains
Transformation Beyond Efficiency
Looking Ahead: Expanding Automation and Integration
Conclusion: The Power of AI and Automation Combined
About the Authors
Transforming Legal Operations: Aderant’s Journey with Amazon Quick
This guest post is co-written by Angela Mapes and Adam Walker of Aderant.
In the rapidly evolving legal industry, effective management of information and processes is crucial for success. Aderant, a leading global provider of comprehensive business management software for the legal sector, has taken significant strides in this direction by leveraging innovative technology. Their 38-member Cloud Engineering team has transformed how they support Expert Sierra, their cloud-based legal practice management solution, by implementing Amazon Quick. This shift has not only accelerated documentation processes but has also empowered the team to provide faster and more responsive support to clients depending on Expert Sierra for their daily operations.
In this post, we’ll share how Aderant harnessed the AI capabilities of Amazon Quick to unify search across six vendor systems and automate documentation workflows, achieving up to 90% faster search times and 75% documentation acceleration. We’ll also discuss how other organizations can adopt similar strategies for improved operational efficiency.
The Challenge: Information Scattered Across Six Systems
Aderant’s Cloud Operations team was grappling with a common yet formidable issue: essential information was scattered across multiple disconnected systems. Engineers relied on several dashboards to find answers, creating substantial operational friction. Manual searches took 30–45 minutes per task, significantly slowing down issue response and troubleshooting times.
With over 200 support tickets arriving daily and a commitment to 24/7 global support, these delays quickly compounded. Engineers were spending precious time scouring for information instead of solving problems, risking the omission of critical context from fragmented documentation. Aderant urgently needed a solution to unify search across their six knowledge systems, automate repetitive documentation tasks, and seamlessly integrate with existing tools without extensive custom development.
The Solution: AI-Powered Search and Workflow Automation
In October 2025, Aderant deployed Amazon Quick, starting with a pilot version of the CloudOps Helper bot. The implementation was swift; full deployment and the Chrome extension rollout were completed by November 2025. By February 2026, the successful launch within the CloudOps team led to the development of the Support Helper bot, which expanded Quick capabilities to an additional 86 team members.
The centerpiece of this transformation was the CloudOps Helper bot, which provided unified AI-powered search across six core knowledge systems. Engineers could now ask natural language questions and receive pertinent answers drawn from Confluence documentation, SharePoint files, Git repositories, Jira tickets, Teams conversations, and Quick Sight dashboards—all from a single interface.
Pre-built integrations allowed for seamless connections between their six major systems and three MCP servers, getting them operational in mere weeks rather than months. The built-in security management, featuring support for Okta SSO and IAM, negated the need for custom access controls while the unified search capability functioned out of the box without requiring custom UI development.
Important Note on Data Usage
It’s crucial to understand that the CloudOps Helper only analyzes Aderant’s internal operational data sourced from various platforms exclusively related to supporting and maintaining the Expert Sierra platform. No client application data or business information is accessed or analyzed.
Beyond search capabilities, Aderant adopted Amazon Quick Flows to automate the creation of knowledge base articles. This automated workflow incorporated duplicate detection, reducing article creation time from one hour to 15 minutes—a 75% savings—while maintaining quality through a human-in-the-loop process.
Additionally, the team utilized Amazon Quick Research for proactive root cause analysis and pattern discovery, aiding in the evaluation of bot usage trends and enhancing documentation quality by identifying knowledge gaps.
Real-World Impact: Resolving Critical Infrastructure Issues
The effectiveness of Quick became evident during a critical networking incident. A client experienced a domain trust failure, which resulted in widespread authentication issues. The complexity of the problem, involving numerous tickets and engineers, made it challenging to piece together the required troubleshooting history.
An engineer turned to the CloudOps Helper bot, requesting an analysis of the client’s engagement history. The bot synthesized information from Microsoft Teams and Jira, providing a comprehensive overview within minutes. What would have taken hours of manual research was completed in a fraction of the time, allowing engineers to focus on new solutions and significantly expediting the resolution process.
Quantifiable Results: Significant Efficiency Gains
The results from adopting Amazon Quick were striking. Querying multiple data sources simultaneously and automating straightforward Cloud Engineer tasks eliminated redundancy, accelerating investigations and enabling faster resolutions:
- 95% reduction in client history research time, from 2–4 hours to 2–3 minutes.
- 90% faster cross-platform search, decreasing from 30–45 minutes to just 3–5 minutes.
- 75–85% acceleration in documentation creation, with output increasing by 200% and backlog shrinking from over 40 articles to fewer than 10.
Adoption rates highlighted the solution’s value, with the CloudOps Helper enjoying a 95% active use among the 38-person engineering team and approximately 80% adoption of the Support Helper during its pilot phase.
Transformation Beyond Efficiency
The capabilities enabled by Quick fundamentally transformed Aderant’s operations. The team now conducts deeper analyses, identifies trends, and makes informed infrastructure improvement decisions. Unified search is no longer a luxury; it’s an integral operational component.
Knowledge management underwent a significant overhaul as fragmented resources were consolidated, enhancing collaboration across the globally distributed team. Unified access to information across time zones ensured the team operated on the same page, regardless of location.
Looking Ahead: Expanding Automation and Integration
Aderant’s success with Quick has created momentum for further expansion. The Support Helper is progressing from 10% testing towards full deployment, with continuous collaboration between CloudOps and Support. The team has identified three new Quick Flows for development, including automated note-taking from Teams conversations and ticket screening for completeness before queue entry.
Conclusion
Aderant’s journey with Amazon Quick demonstrates that simple search capabilities are not enough. The true transformation lies in the combination of AI-powered search and intelligent workflow automation—removing information fragmentation, automating repetitive tasks, and providing cohesive access to knowledge across various systems. This synergy enabled Aderant to reclaim thousands of hours annually, speed up support responses, and profoundly enhance global collaboration.
With results including 90% faster searches, 75% faster documentation, and impressive 95% user adoption, Aderant’s experience underscores a critical lesson: the most significant breakthroughs occur when search and automation work together.
To discover how Amazon Quick can revolutionize your organization’s operations, visit the Amazon Quick website.
About the Authors
Angela Mapes is a Cloud Application Engineer at Aderant with extensive experience in managing AWS infrastructure for the Expert Sierra platform and building chatbots for optimizing CloudOps operations.
Adam Walker serves as the AWS Cloud Operations Manager at Aderant, leading a globally distributed team focused on platform operations, automation improvements, and AI integration.
Peter Chung is a Senior Solutions Architect at AWS, aiding companies in scaling and modernizing their infrastructure.
Stay tuned for more insights into how technology is transforming the legal industry and enhancing operational efficiencies!