Build smarter. Ship faster. With AI + MAS expertise.
Budgets are tight. Expectations are higher than ever. AI can add efficiencies, but without engineering rigor, an adoption plan, impact measurement, and upskilling, AI is just fancy tools with no ROI.
What is MAS EngineeringIQ?
MAS EngineeringIQ is a framework, not a tool.
It combines:
- Best AI tools (battle-tested daily by MAS engineers)
- MAS proprietary accelerators (BacklogIQ, QualityIQ)
- Engineering rigor (guardrails, adoption plans, measurement)
- MAS expertise (Over a decade delivering complex platforms at scale)
The result: AI that delivers real productivity gains with lasting quality, not wasted licenses.
Where we inject AI efficiencies
We help you apply AI where it drives the most impact:
- MAS BacklogIQ – Most teams are flying blind. Our AI assistant helps Product Owners and PMs refine, align, and prioritize so teams build what matters.
- Code Acceleration – AI-assisted coding, refactoring, and documentation boost developer velocity while enforcing standards.
- MAS QualityIQ – Our AI heatmap identifies bug-prone files, unstable modules, and technical debt hotspots, helping teams fix root causes.
- Smarter Testing & Deployment – AI generates unit tests, automates regression cycles, and predicts release risks for faster, safer shipping.
- Continuous Improvement – AI transforms user feedback and tickets into structured improvement insights.
Why EngineeringIQ works
- Proven Impact: Depending on team maturity and application complexity, AI adoption can deliver 10–30% gains in delivery velocity and measurable improvements in quality and cycle time.
- Industry Validation: Microsoft has reported productivity boosts of up to 50% with AI coding assistants; other studies cite 20–30% efficiency gains.
- MAS Proprietary Accelerators: BacklogIQ and QualityIQ tackle backlog blindness and tech debt head-on — two of the biggest sources of wasted effort.
- Responsible AI: Guardrails ensure faster never means riskier.
- MAS-Proven: Our engineers use these methods and accelerators internally, bringing real-world lessons to client engagements.
The framework at a glance
AI Tools + Proprietary Accelerators + Engineering Rigor = Sustainable AI Efficiency
Unlike just buying licenses, EngineeringIQ is a framework for adoption with impact. Whether MAS is building software for you, or enabling your teams to build faster, we ensure AI is applied with rigor, adoption, and measurable ROI.
Ready to turn AI into real engineering efficiency?
Testimonial
AI Credit Scoring & Agricultural Yield Prediction
“This partnership also enabled us to deliver an innovative AI and ML solution that leverages alternative data (such as satellite, behavioral, demographic, and agricultural) to assess farmers’ credit and predict farm yields. By integrating advanced Machine Learning with expertise in credit risk, we’ve established a robust system that helps us manage risk effectively and maintain a healthy credit portfolio.”
CEO & Head of Technology
Challenge
Traditional credit scoring models failed to account for the complex variables influencing small farm performance, such as weather volatility, soil conditions, and access to resources.
Solution
Custom machine learning (ML) and artificial intelligence (AI) models: one for predicting harvest success and another for assessing credit risk.
Result
- Improved yield prediction accuracy enabled smarter capacity planning
- Reduced credit default risk by using AI and alternative data to assess creditworthiness
- Strengthened the institution’s ability to manage its credit portfolio sustainably
- Delivered measurable social impact by extending access to financing for underserved farmers
Testimonial
Custom LLM Solution for Secure Data Access
“It was no small feat to get through a challenging body of work from design to development completion in a short timeframe and in a complex ecosystem that was new to MAS Global”
Managing Director
“MAS Global went over and above our expectations and contributed to improving the general design and quality of our overall code base.”
Vice President
Challenge
Fragmented Information & Workflow Gaps
- Challenges in filtering data specific to each fund without exposing or accessing information from other funds, ensuring full privacy
- Difficult to test and trust system responses.
Solution
- Automated SQL Permissions for secure, dynamic, role-based data access
- Input/Output Caching to support flexible testing (mock LLM, data, or both)
- Flexible Evaluation Module for each component (LLM-as-a-judge, custom metrics, standard metrics like F1 score)
- Connector Optimizations to boost performance
Result
- Secure and dynamic role-based access to sensitive data across multiple investment funds
- Easier and more reliable testing environment using flexible I/O caching
- Improved LLM output evaluation through advanced scoring and feedback loops
- Better overall system stability and reduced risk during AI development
Global Financial
Services Powerhouse
Testimonial
Business System Modernization
“I appreciate the cooperation that each MAS Global team member displayed under such strenuous conditions making the workflow simple and easy.”
VP of OPT BPA-Card
“The system is just perfect.”
CDFO Leadership
Challenge
Increased risk due to outdated system used to submit potential fraud issues, track & correct errors and process cross-business functions.
Solution
Seamless transition to a new data center while upgrading core application code.
Result
- Over 1,100 business users successfully transitioned to the new system
- Significant time savings due to enhanced performance and responsiveness
- Improved system security and increased resilience across the platform
- A scalable foundation laid for future modernization efforts
World-leading
Polymer Producer
Testimonial
Analytics Infrastructure Modernization
“They were flexible in supporting our key objectives that delivered value.”
Sr Manager Data Analytics
Challenge
Low adoption & outdated database infrastructure preventing an efficient reporting.
Solution
- Data architecture design: defined Snowflake structure & permissions
- Data Migration: migrated reports by repointing Azure SQL MI connection
- Report refresh resolution: change of ODBC adapter after stress test emulation
- Automated testing: defined & implemented test framework
- Training: improved the reporting usefulness & visibility by levelling knowledge
Result
- 500+ reports migrated successfully to Snowflake
- From 0 to 300+ automated test cases
- 6X performance improvement
- Improved data governance & increased user adoption
Let’s deliver your new business solution!
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