Agentic AI Governance, Command Center & Enterprise AI Enablement for RKD Group
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About RKD Group
RKD Group is a data-driven fundraising and marketing services organization supporting nonprofit clients through campaign strategy, donor engagement, digital marketing, analytics, and reporting. As RKD expanded its data, analytics, and AI ambitions, the organization needed a structured way to identify high-value AI opportunities, govern adoption, and move from experimentation into repeatable, measurable AI-enabled delivery.
Business Challenge
Experienz’s rapid feature growth and evolving ESG regulations put increasing pressure on its QA processes.
Slow release cycles: Manual and semi-automated testing extended release timelines.
Difficult-to-scale QA: Static test scripts were hard to maintain as regulations and features changed.
High automation overhead: Creating and maintaining automated test suites required significant engineering effort.
Limited risk visibility: The team lacked predictive insights to identify high‑risk areas before failures occurred.
Experienz needed an AI-native, scalable testing solution that aligned with its AWS-based platform and DevOps practices.
Solution Overview
Partner: Mitra AI
Solution: AI-Driven Test Automation Framework on AWS
Solution Type: Generative AI, Test Automation, DevOps Acceleration
Mitra AI designed and implemented an AI-powered test automation framework on AWS that transforms how Experienz creates, executes, and manages tests.
Core Capabilities on AWS
AI-powered test generation with Amazon Bedrock
- •Uses foundation models in Amazon Bedrock to automatically generate test cases from natural language requirements and user stories.
- •Reduces reliance on manual scripting and accelerates test design.
Intelligent test verification
- •AI-driven assertions and validations improve test accuracy and coverage.
- •Reduces false positives/negatives and increases confidence in test outcomes.
Smart, centralised reporting
- •Automated reporting on test execution, coverage, and quality trends.
- •Provides actionable insights for QA and engineering teams to prioritise fixes and improvements.
Predictive analytics for quality risk
- •Uses historical execution data stored and indexed on AWS to identify high‑risk modules before failures occur.
- •Enables proactive, risk-based quality engineering.
CI/CD and DevOps integration on AWS
- •Integrates seamlessly into Experienz’s existing DevOps pipelines.
- •Supports continuous testing across development, staging, and production-like environments.
End-to-end automation
- •Automates the full lifecycle from test creation through execution, reporting, and ongoing maintenance.
- •Minimizes manual effort for repetitive and regression testing.
The solution is built on a scalable, serverless, AI-native architecture on AWS.
Core AWS Services
Amazon Bedrock
Provides managed foundation models for LLM-powered test generation, reasoning, and test optimisation logic.
Amazon OpenSearch Service
Indexes test cases, logs, and execution results to support search, analytics, and predictive insights.
AWS Lambda
Orchestrates test workflows and AI pipelines using event-driven, serverless compute.
Amazon S3
Stores test artefacts, logs, and reports securely and cost-effectively with lifecycle management.
Amazon API Gateway
Exposes secure APIs that enable interaction among the AI framework, CI/CD tools, and external services.
Rainforest QA
Integrates with the AWS-based framework to execute automated test scenarios at scale across multiple environments and configurations.
Mitra AI followed a phased, AWS-aligned delivery approach:
Business Outcomes
Quantifiable Impact: efforts reduced from weeks to days
3× faster end-to-end test creation and maintenance.
Automation cycles have been reduced from weeks to days.
Significant reduction in manual test effort and maintenance overhead.
Higher test coverage and reliability result in fewer defects reaching production
Operational
Benefits
Accelerated release cycles and faster time-to-market for new ESG features.
Improved platform quality and stability for Experienz customers.
Reduced QA tool and maintenance complexity through a serverless, managed AWS stack.
Freed engineering capacity to focus on innovation instead of maintaining test scripts.
Generative AI & Innovation on AWS
This solution highlights how AWS enables practical, high-impact GenAI adoption in software engineering.
With Amazon Bedrock and serverless services, Experienz has:
AI-driven test generation and validation from natural language requirements.
Continuous learning from test execution data stored on AWS to refine scenarios and prioritization.
A shift from reactive QA (finding defects late) to predictive quality engineering (preventing failures early).
Reduced dependency on manual, repetitive testing tasks through automation and AI.
Security & Compliance on AWS
Given Experienz’s role in ESG and regulatory reporting, security and compliance were critical design requirements.
WS-native security controls: The solution follows AWS security best practices, including IAM, VPC isolation, and logging.
No sensitive production data is sent to models; synthetic or masked data is used for AI-driven test generation and validation.
Strict access controls: Fine-grained access to test environments, artefacts, and logs is enforced.
Encryption and governance: Data is encrypted at rest and in transit using AWS-managed keys and governance policies.
COO VALUE
- A scalable, AI-native QA architecture on AWS that grows with the platform.
- Higher confidence in release quality through improved coverage and predictive analytics.
- Seamless integration with existing AWS-based DevOps pipelines.
- A future-ready testing strategy aligned with Experienz’s cloud and ESG roadmap.
CFO VALUE
- Lower QA operational and infrastructure costs through serverless and managed AWS services.
- Faster time-to-market for new ESG capabilities, improving competitiveness and revenue potential.
- Better utilisation of engineering resources, focusing teams on product innovation.
- Higher return on development investment via reduced defects, rework, and production incidents.
Future Expansion on AWS
This engagement demonstrates how AWS enables:
Scalable GenAI-powered QA automation through Amazon Bedrock and serverless services.
Serverless, AI-driven DevOps pipelines with AWS Lambda, Amazon API Gateway, and Amazon OpenSearch Service.
Enterprise-grade adoption of AI in software engineering with robust security, governance, and compliance controls.
Faster delivery of high-quality digital platforms in regulated domains such as ESG and sustainability.
Partner Information
Mitra AI helped Experienz accelerate software delivery by three times with an AI-driven test automation framework built on AWS. By combining Amazon Bedrock with serverless and analytics services, Experienz modernised its QA operations, reduced costs, and increased release velocity—showcasing a repeatable pattern for GenAI-powered quality engineering on AWS.