Hypercubic provides an AI-driven platform that models legacy mainframe environments and captures subject‑matter expert knowledge as a searchable digital twin. The system automatically translates COBOL, JCL, and related assets into modern code, generates synchronized documentation, and offers real‑time AI assistance for debugging and operations, helping enterprises reduce mean‑time‑to‑repair and retain institutional expertise.
Funding
Funding not disclosed
Founders
Product
Problem
Enterprises that rely on legacy mainframe and COBOL applications face high operational risk because critical system knowledge resides in a dwindling pool of subject‑matter experts. When those experts retire or become unavailable, organizations lose the “how” and “why” behind complex batch jobs, leading to prolonged outages, costly manual interventions, and delayed modernization efforts.
Solution
Hypercubic applies agentic artificial intelligence to ingest and model the behavior of mainframe environments, enabling safe transformation of COBOL, JCL, and related assets into modern, maintainable applications. The platform creates a “HyperTwin” – a digital replica of SME expertise captured through AI‑driven interviews and real‑time workflow observation – and a “HyperDocs” knowledge base that auto‑generates structured, continuously synchronized documentation. By combining deterministic analysis with generative AI, Hypercubic delivers accurate code translation, automated documentation, and on‑demand AI assistance for debugging and operations, reducing mean‑time‑to‑repair and preserving institutional knowledge as a searchable asset.
Target Audience
Primary customers are large enterprises that operate mission‑critical mainframe workloads—such as banks, insurers, manufacturers, aerospace firms, utilities, and government agencies—seeking to retain legacy expertise while modernizing their applications.
Features
- Agentic AI engine that parses COBOL, JCL, DB2, and other legacy code to produce deterministic transformation scripts and validation checks.
- HyperTwin digital twin that records SME problem‑solving steps, command sequences, and decision rationale via AI‑guided interview sessions, making tacit expertise instantly searchable.
- HyperDocs auto‑updating documentation layer that extracts system workflows into human‑readable, version‑controlled artifacts synchronized with the live codebase.
- Hybrid deterministic + generative AI workflow that mitigates hallucinations while enabling flexible code refactoring and annotation.
- Deep integration adapters for proprietary mainframe interfaces, supporting batch processing, transaction monitoring, and real‑time command execution.
- Real‑time AI assistance chat that can suggest TSO commands, diagnose abends, and guide remediation without leaving the mainframe console.
- Secure, audit‑ready knowledge repository with role‑based access controls and encryption, suitable for compliance‑heavy industries.
- API and SDK for embedding AI‑driven insights into existing DevOps pipelines and IT service management tools.