Data conversions are far too manual
Companies have moved their data from old to new since the first computer system was retired. Enterprise software has advanced a lot since then, but the process for converting data hasn’t. IT teams and consultants still rely on essential tools like spreadsheets, scripts, and SQL queries. These are labor-intensive and require high-level expertise, extending the timeline for onboarding new applications. This fragmented approach to data conversion is time-consuming and inefficient, resulting in too many projects delivered late and over budget.
Zengines has a better way of converting data with a platform that automates the entire process from end to end. With Zengines, data conversion efforts are faster and less labor-intensive resulting in reduced costs and risk.
AI-powered data conversion rapidly accelerates data analysis, mapping, and testing
Companies migrating to new systems often need more expertise in the new target system. In contrast, software vendors for the new system tend to shift the responsibility for data conversion onto the data owners. This creates a data conversion gap that is challenging to navigate. Questions that customers of new software often ask include:
· How long will it take to convert the data?
· Will there be a gap in the data compatibility and completeness between the two systems?
· Is my source data sufficient to populate the target system
· Will I be able to achieve the business goals we are seeking?
· Do I need to enrich my data from other sources?
· Can my target store all of my current data?
With Zengines, a data conversion project never starts from scratch. Our AI algorithms understand the requirements of the target system. They will automatically analyze the source system's table structures, relationships, and data to automate the data conversion process. The result is a tremendous head start with any data conversion projects and a better understanding of what is required to achieve your business objectives.
How Zengines uses artificial intelligence to accelerate data conversions
- Analyzer: Connect to 45 different databases or ingest multi-format data sets from CSV, Excel, XML, PDF, or APIs
- Analyzer: Classify tables and fields. Automatically build relationships based on primary-key/foreign-key relationships.
- Analyzer: Identify quality issues within source data.
- Mapper: Identify source-to-target field matching.
- Mapper: Detect and resolve data type differences.
- Mapper: Produce field-level logic where data needs to be transformed to meet the requirements of the new target system.
- Loader: Integrated Testing and Validation
Zengines ML models continually improve with each new conversion, offering better results with each data conversion project.
Automating the data conversion process with the Zengines platform
Zengines provides an end-to-end platform, digitizing and streamlining each step of the data conversion process. This integrated approach simplifies the user experience, with inputs and outputs for each step in the process, and they seamlessly flow from step to step until all data is converted. Four technologies underpin the flow of data throughout the process:
- Zengines Data CatalogTM – System migration projects need up-to-date, accurate metadata to identify critical patterns between the source and target systems. Zengines’ intelligent data catalog is rapidly constructed from all source and target system schemas and metadata generated by Zengines Analyzer, providing the foundation for data conversion analysis.
- Zengines Knowledge GraphTM – The Zengines Knowledge Graph is the repository for training our powerful data conversion models. Our patent-pending technology uniquely builds domain-specific models for each industry and commercial software platform we have worked with. Customers benefit from prior data conversion efforts, making the algorithms smarter over time.
- Data Conversion Pipeline – On the Zengines platform, data flows through an integrated process: ingestion à cleansing à transformation à post-processing à loading of data, à reconciliation. Our Data Conversion Pipeline controls the flow of this data as it is prepared for the target system and enables rapid iterative cycles through the pipeline to refine outputs continuously.
- Collaboration and Control – System migration efforts involve many teams, people, and environments, such as Development, Testing, User Acceptance Testing, and Production. Hundreds or even thousands of decisions need to be made and tracked during these projects. Zengines Collaboration and Control module ensures that project users and resources stay organized and can operate from a common source of truth.
Why we load data fast, early and often
Companies migrating to new systems often need more expertise in the target system, while vendors tend to shift the data conversion responsibility onto the data owners. This creates a data gap that is challenging to navigate. To address this issue, it's crucial to adopt a target system-focused approach, starting with the new system's requirements in mind.
Target and downstream system vendors, product owners, and users eagerly wait to see their data within the new system resulting in project delays and waste. Zengines believes in loading data quickly, even if it's not initially perfect, to allow for iterative improvements in data completeness and quality and to drive overall project efficiencies.
Conclusion
Zengines offers an entirely new way of converting data. With an emphasis on speed and repeatability, Zengines combines artificial intelligence and automation to transform manual and time-consuming data conversions into an efficient and predictable process.
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We're excited to unveil our refreshed visual identity, a transformation that mirrors our company's evolution, recent funding success, and expanding product portfolio. This strategic rebrand marks a pivotal chapter in our story, reflecting our company's growth and evolution while honoring the core principles that have guided us from the beginning.
The evolution of Zengines
Born from a vision of technological freedom in 2020, Zengines emerged with a clear purpose: to ensure data maintains its utility and integrity when transitioning between systems to remain valuable regardless of technological evolution. We recognized that companies everywhere were being handcuffed by their data - trapped in legacy systems and hindered by the complex, time-consuming process of data migration. What should have been a straightforward path to digital transformation was instead a journey filled with roadblocks, delays, and frustration.
Our journey began with a powerful AI-driven data migration solution that dramatically simplified how organizations convert and migrate their valuable data end-to-end. As we partnered with more clients, we discovered a critical insight: many businesses couldn't even begin their migration journey because they were paralyzed by "black box" legacy systems. Decades of mainframe COBOL code and undocumented processes had created an impenetrable maze of data paths that no one fully understood.
This revelation led to our groundbreaking Mainframe Data Lineage product, technology that illuminates these black boxes by exposing the hidden data paths, calculation logic, and relationships buried within complex legacy systems. By helping companies understand their current data environment first, we enable them to confidently plan and execute their migration or modernization strategies.
Today, with our recent funding round success, our comprehensive platform addresses the full spectrum of data transformation challenges, from unveiling the mysteries of legacy code to seamlessly migrating data into modern systems. As we've grown from a promising startup to an established technology partner for global enterprises, we needed a visual identity that reflected this evolution and maturity.
Our new visual language
Our refreshed identity system embodies our brand attributes of being trusted, exciting, and hyper-intelligent. The new design system is built around a sophisticated geometric serif logotype that communicates intelligence and innovation.
Our new color palette distinguishes the Zengines brand, adding meaning, energy, and depth to our identity.
A key visual element in our new identity is the Sankey illustration language, which makes visible the invisible connections between systems. Inspired by the fluid connections formed during data migration, this visual element adds movement and reflects the intelligent transformation at the heart of our work – all to maintain data continuity and utility through the inevitability of enterprise and systems change.
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Why this matters
This new identity isn't just about aesthetics - it's a reflection of our growth and maturity as an organization. Our client roster has expanded significantly to include global enterprise organizations that recognize the critical importance of managing data transitions and modernization efforts effectively. These partnerships with Fortune 500 financial institutions, global wealth managers, and leading technology providers have pushed us to elevate every aspect of our business, including how we present ourselves visually.
As we've expanded our capabilities from AI Data Migration to include Mainframe Data Lineage, our visual system needed to convey the sophisticated technology and trusted expertise we bring to solving complex data challenges. Enterprise clients with decades of legacy systems and millions of customer records require a partner they can trust implicitly with their most valuable asset - their data. Our refined visual identity now properly reflects the enterprise-grade solutions we deliver and the confidence our clients place in us.
Our commitment remains unchanged
While our look has evolved, our fundamental mission remains steadfast: to create a world where data retains utility and integrity regardless of technological evolution, and technology decisions are based on business needs - not migration fears or legacy constraints. We remain committed to helping organizations reduce time, cost and risk while ensuring successful project outcomes through our AI-powered solutions that empower the business user.
As we continue to grow and evolve, this new visual identity will serve as a strong foundation for clearly communicating the value we deliver - making complex data migrations and research simpler, faster, and more reliable for our customers.
We will continue to serve our customers with the same dedication and innovation they've come to expect from Zengines, now with a visual identity that better reflects who we are today.
Looking to learn more about our products and capabilities?
Schedule a demo with our team today.
In this episode of The Disruptor Podcast, host John Kundtz interviews Caitlyn Truong, CEO and Co-founder of Zengines.
Mainframe Modernization Prioritization and Challenges
While mainframes are highly performant and reliable, many organizations are seeking to modernize them to de-risk legacy technology.
Mainframe legacy technology is risky to organizations for several reasons, including:
- Code written decades ago with SMEs no longer available
- Fewer people familiar with older programming languages
- Lack of standards in older code making maintenance difficult
According to Caitlyn, "There are more lines of COBOL code in existence than any other programming language," making mainframe modernization particularly challenging.
Zengines Mainframe Data Lineage Product
Caitlyn explains that Zengines' Mainframe Data Lineage product was developed when they discovered a client struggling to modernize because their mainframe was a "black box." The product ingests schemas, metadata, code (including COBOL and JCLs) to create a data lineage information base, helping business analysts understand calculation logic and conditions critical to modernization success.
Zengines' Mainframe Data Lineage product helps organizations understand their legacy systems by providing:
- Interactive research application and data
- Data lineage with graphical visualization
- Relationship mapping between modules, tables, fields, and variables
- Tables and fields inventory with profiling
- Calculation logic analysis
- Branching/conditional statement analysis
Recommendations for Mainframe Modernization Success
Caitlyn's recommendations for mainframe modernization success include:
- Understand what you're converting and the full lineage/interdependencies
- Have a guiding strategy and design - use phased approaches rather than "big bang"
- Employ proper tools for data lineage to answer questions about the system
- Start small with something you know you can convert, then celebrate successes
Her most important advice is to "get started" rather than spending too much time planning: "You'll learn and get more value just by doing."
Listen to the full episode
In today's increasingly regulated financial landscape, banks and financial institutions face mounting pressure to ensure complete visibility and traceability of their Critical Data Elements (CDEs). While regulatory frameworks like BCBS 239, CDD, and CIP establish clear requirements for data governance, many organizations struggle with implementation, particularly when critical information resides within decades-old mainframe systems.
These legacy environments have become the Achilles' heel of compliance efforts, with opaque data flows and hard-to-decipher COBOL code creating significant blind spots. Zengines Mainframe Data Lineage product offers a revolutionary solution to this challenge, providing unparalleled visibility into "black box" systems and transforming regulatory compliance from a time-consuming burden into an efficient, streamlined process.
The Regulatory Challenge of Critical Data Elements
For banks and financial services firms, managing Critical Data Elements (CDEs) is no longer optional - it's a fundamental regulatory requirement with significant implications for compliance, risk management, and operational integrity. Regulations like BCBS 239, the Customer Due Diligence (CDD) Rule, and the Customer Identification Program (CIP) mandate that financial institutions not only identify their critical data but also understand its origins, transformations, and dependencies across all systems.
However, for institutions with legacy mainframe systems, this presents a unique challenge. These "black box" environments, often powered by decades-old COBOL code spread across thousands of modules, make tracing data lineage a time-consuming and error-prone process. Without the right tools, financial institutions face substantial risks, including regulatory penalties, audit failures, and compromised decision-making.
"Financial institutions today are trapped between regulatory demands for data transparency and legacy systems that were never designed with this level of visibility in mind. At Zengines, we've created Mainframe Data Lineage to bridge this gap, turning black box mainframes into transparent, auditable systems that satisfy even the most stringent CDE requirements." - Caitlyn Truong, CEO, Zengines
The Hidden Compliance Challenge in Legacy Systems
Many financial institutions operate with legacy mainframe technology that can contain up to 80,000 different COBOL modules, each potentially containing thousands of lines of code. This complexity creates several critical challenges for CDE compliance:
- Opacity of Data Origins: When regulators ask "Where did this value come from?", companies struggle to provide clear, documented answers from within mainframe systems.
- Calculation Verification: Understanding how critical values like interest accruals, risk assessments, or customer identification data are calculated becomes nearly impossible without specialized tools.
- Conditional Logic Tracing: Determining why specific data paths were followed or how specific business rules are implemented requires manually tracing through complex code branches.
- Resource Scarcity: Limited availability of mainframe or COBOL experts makes compliance activities dependent on a shrinking pool of specialized talent.
- Documentation Gaps: Years of system changes with inconsistent documentation practices have left critical knowledge gaps about data elements and their transformations.
"The challenge with mainframe environments isn't that the data isn't there—it's that it's buried in thousands of COBOL modules and complex code paths that would take months to manually trace. Zengines automates this process, reducing what would be weeks of research into minutes of interactive exploration." - Caitlyn Truong, CEO, Zengines
Introducing Zengines Mainframe Data Lineage
Zengines Mainframe Data Lineage product is purpose-built to solve compliance challenges like these by bringing transparency to legacy systems. By automatically analyzing and visualizing mainframe data flows, it enables financial institutions to meet regulatory requirements without the traditional manual effort.
How Zengines Transforms CDE Compliance
1. Automated Data Traceability
Zengines ingests COBOL modules, JCL code, SQL, and other mainframe components to automatically map relationships between data elements across your entire mainframe environment. This comprehensive approach ensures that no critical data element remains untraced.
2. Visual Data Lineage
Instead of manually tracing through thousands of lines of code, Zengines provides interactive visualizations that instantly show:
- Where data originates
- How it transforms through calculations
- Which conditions affect its processing
- Where it ultimately flows
This visualization capability is particularly valuable during regulatory examinations, allowing institutions to demonstrate compliance with confidence and clarity.
3. Calculation Logic Transparency
For BCBS 239 compliance, institutions must understand and validate calculation methodologies for risk data aggregation. Zengines automatically extracts and presents calculation logic in human-readable format, making it simple to verify that risk metrics are computed correctly.
4. Branch Condition Analysis
When regulators question why certain customer records received specific treatment (critical for CDD and CIP compliance), Zengines can immediately identify the conditional logic that determined the data path, showing exactly which business rules were applied and why.
5. Comprehensive Module Statistics
Zengines provides detailed metrics about your mainframe environment, helping compliance teams understand the scope and complexity of systems containing critical data elements.
"When regulators ask where a critical value came from or how it was calculated, financial institutions shouldn't have to launch a massive investigation. With Zengines Mainframe Data Lineage, they can answer these questions confidently and immediately, transforming their compliance posture from reactive to proactive." - Caitlyn Truong, CEO, Zengines
Real-World Impact: Accelerating Compliance Activities
Financial institutions using Zengines Mainframe Data Lineage have experienced transformative results in their regulatory compliance activities:
- 90% Reduction in Audit Response Time: Questions about data calculations that previously took weeks or months to research can now be answered in minutes.
- Enhanced Confidence in Regulatory Reporting: With the ability to see, follow, and explain data origins and transformations, institutions can ensure the accuracy of regulatory reports.
- Reduced Dependency on Specialized Resources: Business analysts can now answer many compliance questions without requiring mainframe expertise.
- Improved Risk Management: Comprehensive visibility into how critical risk metrics are calculated enables better oversight and governance.
- Future-Proofed Compliance: As regulations evolve, having comprehensive data lineage documentation ensures adaptability to new requirements.
Beyond Compliance: Strategic Benefits
While regulatory compliance drives initial adoption, financial institutions discover additional strategic benefits from implementing Zengines Mainframe Data Lineage:
- System Modernization Support: The detailed understanding of data flows facilitates safer, faster and more accurate modernization from legacy systems - this may include requirements gathering, new development, data migration, data testing, reconciliation, etc.
- Operational Efficiency: Rapid identification of data dependencies reduces development time for system changes.
- Risk Reduction: Comprehensive visibility into mainframe operations reduces operational risk associated with mainframe management and changes.
- Knowledge Preservation: As mainframe experts retire, their implicit knowledge becomes explicitly documented through Zengines.
"What we've discovered working with financial services firms is that CDE compliance isn't just about satisfying regulators—it's about fundamentally understanding your own critical data. Our Mainframe Data Lineage solution doesn't just help banks pass audits; it gives them unprecedented insight into their own operations." - Caitlyn Truong, CEO, Zengines
Getting Started with Zengines
For financial institutions struggling with CDE compliance across legacy systems, Zengines offers a proven path forward. The implementation process is designed to be non-disruptive, with no modifications required to your existing mainframe environment.
The journey to compliance begins with a simple assessment of your current mainframe landscape, followed by automated ingestion of your code base. Within days, you'll have unprecedented visibility into your critical data elements – transforming your compliance posture from reactive to proactive.
In today's regulatory environment, financial institutions can no longer afford the uncertainty and risk associated with "black box" mainframe systems. Zengines Mainframe Data Lineage brings the transparency and traceability required not just to satisfy regulators, but to operate with confidence in an increasingly data-driven industry.
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