Pangram, a startup founded by former Tesla and Google engineers, has raised $4 million in seed funding to scale its platform for detecting AI-generated text. The company is positioning itself as a key player in a rapidly growing space as schools, media outlets, and enterprises seek reliable tools to distinguish human writing from machine-generated content.
The funding round was led by ScOp, with participation from Script Capital and Cadenza Ventures. Pangram had previously raised a pre-seed round from Haystack VC, bringing its total funding to date to just over $4.25 million.
Founded in 2023 by Bradley Emi, formerly of Tesla, and Max Spero, a former Google engineer and Stanford alumnus, Pangram is tackling one of the most pressing challenges in the age of generative AI: the erosion of content authenticity. The company uses proprietary active learning algorithms and open-source large language models to analyze text and determine its likely origin.
“Our goal is to build affordable, high-accuracy systems that anyone can use to audit content at scale,” Pangram wrote in a recent company update. Unlike some competitors that rely on watermarking or behavioral fingerprinting, Pangram’s model focuses on linguistic and statistical signatures—making it adaptable as AI text generation evolves.
The platform has already onboarded a number of paying customers, including Quora, NewsGuard, and several education-sector pilots. Pangram offers tiered pricing: $15/month for individuals with up to 600 scans, and professional plans for educators and developers starting at $45 and $100/month respectively.
The company currently has a team of eight, with plans to double its headcount in the next 12 months. Funds from the seed round will be used to further develop its core detection engine, roll out integrations with enterprise software tools, and support expansion into international markets.
Pangram enters a crowded but critical market, with players like GPTZero, Originality.ai, and Turnitin also racing to offer dependable detection solutions. But investors and early adopters point to Pangram’s technical precision, speed of updates, and low compute costs as key differentiators.
As the boundaries between human and machine-written content continue to blur, tools like Pangram’s are expected to become increasingly important for maintaining trust, transparency, and intellectual integrity in both academic and corporate environments.