AI writes code. EltegraAI turns intent into governed software.
Modernize legacy systems. Build agents, applications, and integrations at factory scale.
Patent-pending knowledge graph — 99.9%+ accuracy.
Named a 2026 Intellyx Digital Innovator — selected from hundreds of briefings.
Three Production Lines
Modernize Legacy Systems
Reconstruct intent from COBOL, Java, SAP, PowerBuilder, and more. Generate verified requirements and modern cloud-ready code — fully traceable from legacy to every new artifact.
COBOL to C#: 18.5 months → 3.5 months
Build Products from Intent
Describe the outcome you want in plain English. EltegraAI interviews you, generates a complete governed spec, and streams it to a coding agent that builds the working product.
One brief → 2,988 requirements,
8,400 test cases
Turn Workflows into Agents
Manual, repetitive enterprise workflows become autonomous agents. Capture business rules and decision logic, generate governed specs, build agents with built-in traceability and oversight.
Customer onboarding: 2–3 weeks → hours
Why the Knowledge Graph Outperforms Generic AI
Unlike most AI-based modernization tools that rely on semantic search and probabilistic retrieval, EltegraAI builds a dependency-linked knowledge graph representing the actual structure and behavior of the application. This eliminates the gaps and inconsistencies inherent in competing approaches and enables complete reconstruction of enterprise system intent — even for multi-million-line codebases — achieving 99.9%+ accuracy.
Highly Accurate Logic Extraction
Patent-pending approach. No semantic search gaps. 99%+ accuracy.
Multi-Pass Validation
Multiple extraction passes. Far beyond the 60–75% typical of LLM-based tools.
Multimodal Inputs
Source code, docs, Jira, meeting transcripts, stakeholder interviews — all in one graph.
Intent-Driven Output
Frozen intent model validates system behavior before generating a single line of code.
Legacy Systems Are Holding Your Enterprise Back
Enterprises spend $1–2 trillion annually on transformation. Nearly 70% stall or fail.
Legacy systems are opaque, poorly documented, and stripped of institutional knowledge.
When COBOL specialists retire, decades of business logic leave with them.
AI coding agents fail on legacy because they're translating code line-by-line — not understanding intent.
