FalsoAI – Detect influence/manipulation patterns in content
Cybersecurity for your brain sounds compelling, but the MVP lacks technical depth.

Psycho-security is a compelling angle, but this MVP lacks technical differentiation.
Media consumers concerned about manipulation
Ground News · Media Bias Fact Check · NewsGuard
In a way, it is similar to what an antivirus does for a computer, but applied to human cognition.
This simple project is mainly an MVP proof of concept.
I want to turn this project into an entire ecosystem to give people more control, detect PSYOPS, election manipulation, and give people more awareness.
Right now all the marketing companies are getting very good an influencing people, and this is going to get worst with LLMs.
All the innovation is going into marketing, and nothing is going into giving people more control over their devices and their lives.
I want to build this ecosystem to serve as a counterweight, ensuring we don't live in a future where big companies control people's behavior. (not gonna let them do that)
this is the website: https://www.falsoai.com/
these are some test examples that you can try:
YouTube
https://www.youtube.com/watch?v=2sQbK6EH9yg&t=2379s
https://www.youtube.com/watch?v=pDxCC5-C9Tg&t=128s
https://www.youtube.com/watch?v=MZPVPCIeUpg
News
https://edition.cnn.com/2026/04/22/us/epstein-files-sex-traf...
https://www.bbc.com/news/articles/cn0ep28drllo
https://edition.cnn.com/2026/04/21/economy/us-retail-sales-m...
Thanks for taking a look. I would really appreciate any feedback and suggestions!!! :)
Cybersecurity for your brain sounds compelling, but the MVP lacks technical depth.
Detects 10 tactical patterns without Stockfish—clever heuristics, tiny audience.
Visualizes feed manipulation on 7 platforms, but lacks depth beyond percentage breakdowns.
Distribution shape analysis beats average star rating for spotting engineered reviews.
This forces LLMs to play inside a deterministic CBT pipeline — it extracts distortion signals, calibrates emotional intensity, applies rule-based risk tiers, then generates tone-locked replies with word caps. The split between deterministic detection and constrained drafting is smart and makes outputs more auditable; Reflect vs Assist modes show sensible product framing. Promising concept for safety-minded builders, but the real value hinges on the model tuning and risk-handling under real conversations, not the attractive landing UI.
Nine detection methods run client-side when Power BI requires cloud uploads.