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Automate any workflow using plain english
RetroFix has raised $500K across 1 funding round.
Key people at RetroFix.
RetroFix was founded in 2024 by Daniel Portela (Co-Founder, CTO) and Isaac Toscano (Founder).
RetroFix has raised $500K in total across 1 funding round.
RetroFix is an automation platform designed to be extremely intuitive to use, making it much easier and faster to automate manual work.
To create or modify workflows you can describe them in natural language and our agent will create them end-to-end for you. We allow you to connect with 2000+ applications and use our pre-built actions for your workflows. In the case we don't have a pre-built step, our agent can instead write code to access the full APIs of all the apps we integrate with.
RetroFix AI is a cloud-based automation platform that enables users to create and manage workflows using plain English instructions, eliminating the need for coding. It primarily serves contractors, building owners, and HVAC professionals by automating the application process for energy efficiency rebates and subsidies, helping them save time and money. The platform connects to over 2,800 apps, allowing seamless integration and rapid workflow deployment. By simplifying complex regulatory and subsidy processes, RetroFix AI addresses a critical barrier to building decarbonization and energy efficiency improvements, contributing to sustainability goals while accelerating clean energy adoption in the built environment[2][3][4][5].
Founded by Isaac and Daniel, who met at MIT two years prior, RetroFix AI emerged from their shared commitment to tackling building decarbonization—the fourth largest global source of carbon emissions. They identified the cumbersome and opaque process of securing government subsidies for energy-efficient building upgrades as a major obstacle. The company started by focusing on streamlining subsidy applications in New York City, where utilities like Consolidated Edison have deployed billions in incentives. Early traction came from automating these applications, reducing manual effort for contractors and ensuring compliance with evolving regulations. This foundation set the stage for broader impact in the energy transition space[4].
RetroFix AI rides the growing trend of AI-driven automation and natural language interfaces, which democratize technology use by removing coding barriers. The timing is crucial as global and local governments increase regulatory pressure and financial incentives for building decarbonization to meet climate goals. Market forces such as rising carbon emissions regulations, expanding subsidy programs, and the urgent need for energy-efficient infrastructure create strong tailwinds. By simplifying subsidy access and automating workflows, RetroFix accelerates the adoption of clean energy technologies, influencing the broader ecosystem of contractors, building managers, and sustainability-focused startups[4].
Looking ahead, RetroFix AI is poised to expand beyond New York City, scaling its platform to serve more regions and sectors within the building and energy efficiency markets. Trends like increasing regulatory complexity, growing AI capabilities, and heightened climate action commitments will shape its journey. As the platform evolves, its influence may extend to broader workflow automation use cases beyond energy subsidies, potentially becoming a key enabler of operational efficiency in sustainability and other industries. RetroFix’s mission to make automation accessible through plain English positions it well to lead in the convergence of AI, automation, and climate tech.
RetroFix was founded in 2024 by Daniel Portela (Co-Founder, CTO) and Isaac Toscano (Founder).
RetroFix has raised $500K in total across 1 funding round.
RetroFix's investors include Y Combinator.
Key people at RetroFix.
RetroFix has raised $500K across 1 funding round. Most recently, it raised $500K RetroFix AI - Seed in September 2024.
| Date | Round | Lead Investors | Other Investors |
|---|---|---|---|
| Sep 1, 2024 | $500K RetroFix AI - Seed | Y Combinator |