Model ML completes finance work more efficiently with GPT-5.6 Sol

Before financial analysis can stand up in front of clients or senior decision-makers, teams have to carry it through a demanding last mile: reconciling evidence, building and formatting the file, checking every number, and linking each claim to its source. The finished PowerPoint deck or Excel workbook has to be editable and ready for scrutiny.

Model ML cofounders and brothers Arnie and Chaz Englander saw how much work that required when, after two successful exits, they began investing through a private family office and, as builders do, building software to help themselves.

Grown out of that software, Model ML’s agents help finance professionals carry a workflow from the initial request through research, analysis, and a finished deck or workbook. At the center, a core agent plans the work, selects the right tools, reconciles evidence, and runs calculations, routing each step to the model best suited to it, which is often GPT‑5.6 Sol. Among those tools is Model ML’s own document tooling, which creates native PowerPoint and Excel files with traceable sources.

“Earlier models could do the work of an analyst, but the user would have to clearly break down the task, specifically what it wanted the output to look like. With GPT-5.6 Sol, we’re finding that the agent gets far closer to the final output.”

—Chaz Englander, Co-founder and CEO at Model ML

Solving the last mile of finance work

Model ML helps finance teams by automating finance workflows end to end. From a brief and source material, the agent can carry an assignment through research and modeling to finished materials for clients or deal teams. The finance professional checks the assumptions, sources, and message before sharing the work.

Model ML calls the product “surface-agnostic.” A finance professional can start an assignment in email, or the Model ML app, and continue it in its Microsoft Office plug-ins without explaining it again.

—Chaz Englander, Co-founder and CEO at Model ML