Diverger builds mission‑driven AI systems that orchestrate autonomous agents to modernize and operate legacy software. Their platform iteratively learns, turning tasks that once took days into hour‑long processes and cutting manual effort by up to 60%. By replacing legacy code with AI‑directed workflows, Diverger enables senior teams to focus on strategic outcomes rather than maintenance.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises with legacy codebases in languages such as COBOL, PL/SQL, and VB6 face high manual effort and long migration timelines when trying to modernize their software, often risking functional loss and operational disruption.
Solution
Diverger provides a mission‑driven AI platform that lets senior teams design and orchestrate autonomous agent systems to modernize legacy applications. The platform’s agents iteratively learn to translate legacy code into modern architectures while preserving 100 % functional parity, reducing manual effort by up to 60 % and shrinking migration cycles from weeks to hours. Users define clear objectives, success metrics, and governance rules, then direct the agents to execute, self‑supervise, and self‑correct throughout the transformation. The resulting modern core integrates with existing data and processes, enabling continuous improvement without the need for extensive re‑coding.
Target Audience
Primary customers are large enterprises and organizations that rely on critical legacy software and need a controlled, low‑risk path to modern, self‑improving systems.
Features
- Autonomous agents that iteratively learn to convert COBOL, PL/SQL, VB6, and monolithic systems into modern architectures
- Design workflow where senior teams specify mission objectives, metrics, and governance from the outset
- Self‑supervising execution layer that monitors and corrects agent actions in real time
- Preservation of 100 % functional parity between legacy and modernized code
- Integrated analytics showing manual effort reduction (‑60 %) and time savings (days to hours)
- Enterprise‑wide deployment (Gemini Enterprise) with built‑in data connectivity and governance controls