Brain.fm vs NEDIO

Brain.fm. Its site says its music is composed by humans. Its science page describes a process in which human composers create the music and Brain.fm’s technology adds modulation to it, with AI enhancement described as part of that. It says its music is not binaural beats and that it applies modulation directly in each stereo channel. So “AI-generated” is not an accurate description of Brain.fm’s music, and an earlier version of this page was wrong to use it.

NEDIO. NEDIO’s audio is AI-generated. We produced it with a third-party generative music tool and assembled the tracks into continuous mixes. It is not recorded by performers or licensed from a music library, and NEDIO makes no claim of modulation or entrainment. See our terms for how the audio is licensed to you. If human-composed music matters to you, that is a real difference between these products.

What the evidence covers. Brain.fm cites its own and supporting research. A 2024 peer-reviewed study in Communications Biology by Woods and colleagues tested music with amplitude modulation added at specific rates. It found that modulation sustained attention differently for people with different levels of attentional difficulty, and that beta-range modulation helped more than other ranges for participants with more ADHD symptoms (DOI 10.1038/s42003-024-07026-3). It is a laboratory study of modulated music, not a test of the Brain.fm product on developers’ work, and a 2026 author correction exists that we have not reviewed. We have not checked the authors’ ties to Brain.fm, so read the paper’s disclosure statement. NEDIO makes no comparable claim. For what studies show about music and noise more broadly, see best music for coding.

NEDIO fits when the bottleneck is the start and the finish of a coding block. You write a goal and a done-when line, the timer and audio start together, and the close-out records whether the goal was reached and what to pick up next. The audio is deliberately a single stream so there is nothing to choose.

It does not read your code, verify that anything passed, or tell you whether the music helped. It records what you tell it. It is also narrower than Brain.fm on purpose: no sleep, no relaxation, no mobile app.

I used Brain.fm for a week and NEDIO for a week. Brain.fm has a large choice of music, and it suits people who want to choose between different options. For me, choosing has always been the problem. Before starting any task I spend time picking a playlist, a service, or a YouTube channel, and that time is gone before the work begins.

NEDIO gives you one stream. You cannot choose the music or tune it. But the audio is of high quality and it did its job well: it kept me focused. What decided it for my workflow was the structure around the audio. NEDIO has a stronger system for managing coding sprints, plus analytics on what I did, what worked, and what did not.

I noticed my productivity went up because of the rituals, not because of the music on its own: a named goal, a timer that ends, and a close-out that records the result.

One five-workday week per product, on the same kind of task (pull requests, or feature work), at roughly the same time of day. Change only the audio and timer layer. Log these every working day:

The first line is the one most comparisons miss. If choosing audio costs you ten minutes a day, a product that removes the choice has a measurable effect even if the sound is no better.

Limits to respect. The week you try second has an advantage or a disadvantage from familiarity, so swap the order with a colleague or add a third week with the first product. A new tool is more interesting than an old one for a few days. You know which product you are using, which colors your ratings. Workload differs between weeks. Self-rated focus is noisy. Two weeks tell you whether you can live with a product’s limits and whether the start routine changed. They do not show an effect on focus.

If the two weeks look the same, keep the cheaper or simpler setup and look upstream of audio: meetings, review latency, unclear tickets. For a longer log tied to audio type, see the two-week audio log.