BotMan AI maps legacy systems to graphs for autonomous re-architecture
The firm uses knowledge graphs to capture business context, enabling agents to rebuild old applications without manual code translation.
Key points
- BotMan AI employs an AI-powered pipeline that maps dependencies and logic into knowledge graphs.
- The approach re-architects systems rather than simply translating old code into newer languages.
- Alejandro D’Andrea states that providing reusable context is more critical than raw intelligence for agents.
BotMan AI is deploying knowledge graphs to facilitate the modernization of legacy software systems. According to SiliconANGLE, the company uses an AI-powered migration pipeline that maps an application’s dependencies, business logic and data models. This method allows autonomous agents to interpret the systems they are rebuilding, providing necessary context that raw intelligence alone cannot supply.
System Context
Legacy modernization requires understanding how an application’s code, data and business rules fit together before rebuilding it. BotMan AI addresses this by representing how application components and rules relate to one another. Alejandro D’Andrea, founder and chief technology officer, explains that the core issue is context, not intelligence. Agents require explicit explanations of tasks, but knowledge graphs allow them to already know the relevant information.
Migration Process
The process involves ingesting entire old code bases, such as those in Delphi, Visual Basic or Oracle Forms. Instead of simple translation, the system re-architects the entire structure autonomously. Knowledge graphs play a significant role in this ingestion phase. They map relationships when information enters the system, reducing the discovery work needed for subsequent queries and enabling full autonomous migration.
Targeted Systems
The technology targets legacy applications built in older frameworks including Delphi, Visual Basic and Oracle Forms. These systems are migrated by rewriting them into a new architecture. The knowledge graph approach is designed to handle the complexity of these specific legacy environments. It aims to replace the need for manual, line-by-line code translation with a holistic architectural rebuild.
Operational Steps
- Ingest the entire legacy application at once to capture all dependencies.
- Map business rules and data models into a structured knowledge graph.
- Use the graph to provide reusable context for AI agents during migration.
- Allow agents to interpret the system autonomously based on mapped relationships.
Background: AI agents
AI agents matter for security because they move beyond generating text to executing code and accessing systems. This autonomy means a single compromised prompt can trigger cascading failures across your infrastructure, requiring new controls for intent verification and action boundaries rather than just content filtering.
Read the full guide: Why AI Agents Matter for Security: Autonomy Risks
What to do and how to stay safe: BotMan AI
- Audit legacy code bases for complex dependencies before attempting modernization.
- Document business rules and data relationships explicitly for AI ingestion.
- Evaluate tools that use knowledge graphs for architectural mapping.
- Monitor for autonomous migration errors during the re-architecture phase.
Step-by-step guide: Prevent Business Logic Vulnerabilities: 4 Proven Measures
General security guidance from the TechSec Observer newsroom. It is not confirmed advice from the organisations named in this story.
Frequently asked questions
How does BotMan AI handle legacy code modernization?
It uses an AI-powered pipeline that maps dependencies and logic into knowledge graphs to re-architect systems autonomously.
Why are knowledge graphs important for this process?
They provide reusable business context, allowing AI agents to understand relationships without manual explanation for every task.
Which legacy languages does this technology support?
The system is designed to migrate code bases from Delphi, Visual Basic and Oracle Forms into new architectures.
