New & production-proven

Atlas: Human Expertise, Captured in Machine Intelligence

Atlas performs a context-aware analysis of mainframe code to provide an unprecedented degree of actionable intelligence. Built on the production-proven Deterministic Machine Learning Engine that powers CloudFrame's COBOL-to-Java conversion, Atlas exposes deep, expert-level understanding, delivering insights no generative AI can match.

Built on CloudFrame's Deterministic Machine Learning Engine, already trusted for large-scale COBOL-to-Java modernization in production environments.

Atlas sample interaction

Mainframe.app

U

You

"Which programs read or write VSAM files?"

A

Atlas Context-aware

CFBOOKSV reads the VSAM file VSAMBOOK to produce reports. In the trading flow, TRDPB programs interact with VSAM and DB2 structures for transaction persistence and lookup, which Atlas traces at the file and field level.

U

You

"Explain what business function the JCL job ACCPEUR performs end-to-end, and flag anything that looks risky to change."

A

Atlas Context-aware

ACCPEUR runs the EUR currency batch cycle by invoking TRDPROC, which drives the core trading programs (TRDPB00x) using EUR-specific runtime parameters (CARD/SYSIN). It validates and enriches orders, performs settlement updates, and produces operational outputs/reports. Risky to change: runtime parameters and step ordering (can change behavior per currency), settlement update logic (balances/positions), restart/idempotency controls, and file/table layouts referenced across multiple steps.

U

You

"Explain what business function program TRDPB000 performs and flag anything risky to change."

A

Atlas Context-aware

TRDPB000 acts as the front door for the trade pipeline: it validates incoming orders, derives routing/classification values (e.g., exchange), and prepares records for downstream settlement. Risky to change: validation rules (can alter acceptance rates), exchange derivation/routing (can redirect trades), record layout passed downstream (breaks TRDPB002 and reports), and any error-handling branches that impact rejection vs retry behavior.

Context awareness Encoded human expertise Business intent recovery

The Atlas Difference

The deterministic Machine Learning model at the heart of Atlas was painstakingly trained by top mainframe experts. It achieved what we are calling "encoded human expertise," giving it full context awareness. True contextual understanding is our biggest feature differentiator, and it is one of the things that enables the DML Engine to figure out the business intent behind legacy code.

The ability to maintain context awareness also allows Atlas to parse unconventional coding styles, unorthodox methods and just about every quirk present in a typical decades-old application. More importantly, because of its enormous context window, the model can process massive code bases, delivering results at enterprise scales. This allows it to not only uncover business intent but to also recover and maintain lost tribal knowledge, a key requirement in an age of rapidly retiring SMEs.

Why it matters

Encoded human expertise

Deterministic models trained on real-world modernization projects, not synthetic code labs.

True context awareness

Sees the entire application landscape, not just isolated programs or files.

Enterprise-scale insight

Handles unconventional patterns and decades of change to recover lost tribal knowledge.

"The data needed to train a GenAI model to do what CloudFrame Atlas can do is not available — it simply doesn't exist in any accessible manner."

SD

Steven Dickens

CEO and Principal Analyst | HyperFRAME Research

Don't Gamble with AI Hallucinations

What Atlas can do is far beyond what the best gen AI models of today can accomplish, and that will continue to be true until a major paradigm shift in how gen AI operates takes place. When it comes to your mission critical legacy systems, you need accurate intelligence that you can trust, and Atlas is the only tool on the market that can deliver it.

Proven in Fortune 100 environments

The same engine that powers production-proven code modernization.

Human expertise encoded

Deterministic ML model trained under human supervision, not just mass data ingestion.

Explainable, not opaque

Every insight traceable back to specific lines of code.

Fast, reliable, actionable

From question to clarity in seconds.

One engine. Two breakthroughs.

Code conversion and code comprehension.

The deterministic ML engine behind CloudFrame's Modernization Suite—the only technology proven in Fortune 100 environments to automatically convert COBOL into 100% functionally equivalent Java was trained, tuned, and guided by human experts. This captured human expertise eliminates the uncertainty of Gen AI and allows the tool to understand not only the functional rules of code, but the business logic and intent (the why behind the how).

Without that understanding, fully automated conversion would be impossible, but its potential does not end there. Seeing a need to fill the gap created by retiring experts, CloudFrame engineered a Living Knowledge Graph accessible to humans via natural language interface, restoring decades of lost institutional knowledge in minutes.

The result…Atlas.

Proven machine learning technology combined with the latest and greatest in gen AI

Long track record of successful projects at numerous high-profile clients

A depth of understanding that no one else can match

No AI hallucinations, guaranteed

Our Technology — The CloudFrame Difference

Two groundbreaking innovations working together to deliver unmatched code intelligence

Deterministic Machine Learning Engine

Production-proven since 2018

The revolutionary technology that got us started and funded is at the heart of every CloudFrame product.

Guided by human experts during its training, the model gained an unprecedented understanding of COBOL systems. We call this understanding "Encoded Human Expertise".

This technology is proven in production at high profile client sites since 2018.

Human-Supervised Training Fortune 100 Proven Context-Aware

Living Knowledge Graph

Verifiable & Enrichable

Our Deterministic Machine Learning Engine gains a deep understanding of COBOL applications, including context, and feeds it into our Knowledge Graph.

The knowledge graph only contains correct and verifiable information. Our customers are never reliant on Gen AI for anything other than making information available in human-readable formats.

The Knowledge Graph also allows SMEs to add context that is not in the source code.

Verifiable Data SME Enrichment No Hallucinations

Semantic Bridge

Human-Readable Intelligence

We developed an innovative mechanism that can access our Living Knowledge Graph and make its data available to human beings and LLMs.

It connects code-level facts to natural language so that users can query by meaning, not by raw COBOL or keywords, allowing for context sensitive information retrieval.

The Semantic Bridge enables the creation of in-depth documentation, BRDs and other technical data and allows LLM-based AI SMEs to answer using graph-backed facts, improving accuracy and eliminating hallucinations.

Natural Language Query Context-Sensitive Graph-Backed Facts

Automated Code Converter

No Vendor Lock-In

A key component of CodeNavigator, this technology uses the deep, context rich data stored in the Living Knowledge Graph to convert COBOL applications into functionally equivalent, human readable and maintainable Java.

This code can be deployed on any platform and is free from any sort of proprietary libraries—you own your code, there is no vendor lock-in.

It is proven in production at high profile client sites since 2018.

COBOL to Java 100% Ownership Production-Ready

Together, these technologies form the foundation of Atlas—delivering trustworthy intelligence from your legacy systems without the risks of AI hallucinations.

Atlas Features & Capabilities

Knowledge Preservation & Risk Mitigation

BRDs, Tech Specs, System Diagrams, and Modernization Roadmaps allow team members to self-serve to remove delays, or leverage the AI SME to focus on what matters most.

Improved Planning

Automated discovery, risk heatmaps, rule-derived test scenarios, and performance insights drive faster test readiness, lower defect leakage, and reduced rework.

Proactive Technical Debt Reduction

Atlas identifies dead code, poor COBOL constructs, and performance bottlenecks, empowering teams to reduce technical debt.

AI SME

Question:

"What dependencies does the PAYROLL module have on external systems?"

Atlas Response:

The PAYROLL module interfaces with 3 external systems: HR_MASTER (employee data), TAX_ENGINE (withholding calculations), and BANK_INTERFACE (direct deposit processing).

Risk Heatmap

Low: 85%

Med: 45%

High: 12%

Code complexity and change risk across 2,847 programs analyzed

Business Requirements

1.0

Customer Account Management System processes daily transactions and maintains account balances.

1.1

System must support real-time balance inquiries with sub-second response times.

1.2

Batch processing window limited to 4 hours for end-of-day settlement.

Auto-generated from legacy COBOL codebase analysis

The Larger and More Complex Your Applications, the Better Atlas Distinguishes Itself

Rather than breaking code down into smaller units or other attempts to overcome Gen AI's limited context window, Atlas' Agentic AI works with massive code bases (the more, the better) to see the big picture, to understand your applications from the smallest detail of a single program to the largest and most complex web of interdependent jobs. And because it is goal and context aware, Atlas continuously learns, adapts and improves, based on both its own agentic feedback loops and optional human SME guidance.

See Atlas in Action

Watch recorded demos showcasing Atlas' major capabilities with real-world examples

AI Subject Matter Expert

Ask natural language questions about your codebase and get instant, context-aware answers from Atlas' AI SME.

Natural Language Context-Aware

Business Requirements Documents

Automatically generate comprehensive BRDs from legacy code, capturing business logic and requirements.

Auto-Generated Business Logic

Technical Documentation

Create detailed technical specs and system diagrams that capture the full architecture and dependencies.

Tech Specs System Diagrams

Ready to see Atlas work on your codebase?