Haladir

Product & Competitive Intelligence

Automates COBOL modernization with formally verified AI that guarantees translated code is correct.

Company Overview

Builds an AI-powered mainframe modernization platform using RL, LLMs, and formal verification (TLA+) to automate documentation, translation, and verification of legacy codebases like COBOL for regulated enterprises.

Competitive Advantage & Moat

Product Roadmap & Public Announcements

Rosetta AI suite for automated legacy code documentation and COBOL translation. Open-sourced Specula (TLA+ spec synthesis), Mobol (mainframe transactions), and OR-bench-sample. Positioning as "verifiable operational superintelligence."

Signals & Private Analysis

Formal verification tooling and operations research benchmarks signal investment in correctness infrastructure. RL environments for proprietary training. Enterprise financial services pilots imminent.

Product Roadmap Priorities

LLM-driven code translation
Improving
Product Differentiation
Engineering

AI-powered automated translation of legacy COBOL codebases into modern programming languages with formal correctness guarantees.

In Plain English

It automatically rewrites ancient bank software into modern code and mathematically proves the new version does exactly the same thing.

Analogy

It's like hiring a translator who not only converts an ancient legal contract from Latin to English but also has a notary stamp proving every clause means exactly the same thing.

Verified RL for code models
Improving
Risk Reduction
Data

Building reinforcement learning environments with formally verified reward signals to train AI coding models that produce provably correct outputs.

In Plain English

They built a training gym for AI where the AI only gets a gold star if a math proof confirms its code is actually correct.

Analogy

It's like training a self-driving car in a simulator where the laws of physics are mathematically perfect, so when it hits the real road, it already knows exactly how to behave.

LLM-powered code documentation
Improving
Operational Efficiency
Operations

AI-driven automated documentation and business logic extraction from undocumented legacy mainframe codebases to preserve institutional knowledge.

In Plain English

It reads millions of lines of ancient, uncommented bank code and writes a plain-English manual explaining what every part does and why.

Analogy

It's like an archaeologist who can read every hieroglyph in a pyramid, then write a guidebook so clear that a tourist could rebuild it from scratch.

Company Overview

Key Team Members

  • Joseph Tso, Co-Founder
  • Preston Schmittou, Co-Founder
  • Quan Huynh, Co-Founder
  • Jibran Hutchins, Co-Founder

Joseph Tso (Princeton, IEEE/Elsevier published), Preston Schmittou (Carnegie Mellon), Quan Huynh (UVA). Uniquely combines formal verification (TLA+), RL, and operations research to guarantee correctness in AI code transformation. Regulated industries need mathematical proof that translated code preserves business logic.

Funding History

  • 2024-2025 | Haladir founded.
  • 2025 | Accepted into Y Combinator; launched Rosetta.
  • 2025 | Open-sourced Specula, Mobol, OR-bench-sample.
  • 2026 | Pre-Seed stage.

Competitors

  • Legacy Modernization: IBM watsonx Code Assistant, Micro Focus, Astadia, TSRI.
  • AI Code: Sourcegraph, Tabnine, GitHub Copilot.
  • Mainframe AI: Phase Change Software, CodeLogic.
  • Formal Verification: Academic/stealth startups.