On 2025-06-24 09:27, evabouchard38--- via NANOG wrote:
Hi all,
I'm part of a postgraduate team at Dublin City University working with Chirp, a startup developing real-time, embedded child-protection software for telecom operators. The solution analyzes data traffic on children’s devices to block harmful content and alert parents to risks such as grooming, cyberbullying, or self-harm — all while respecting privacy and working natively within telco infrastructure.
As part of our MSc practicum, we’re seeking feedback from telecom and network professionals on the commercial, technical, and regulatory feasibility of such an approach.
Would you be open to completing a short, 10-minute questionnaire?
🔗 https://dcusurveys.qualtrics.com/jfe/form/SV_8oBhWiZMRrUh1zM
From the content of the survey and your website, your team seems well aware of where your app sits in the network stack: on the user's device, not in telco space. Honestly, the survey reads a bit like a sales pitch to residential ISP product managers. I'm mildly curious what they would think of offering this app. Does your solution require equipment deployed on the ISP network?
We’d be very grateful for your insights. Happy to follow up with more technical or contextual details if helpful.
Personally, I haven't found any value in my home ISP's value-added services (like Norton Anti-Virus). But that would certainly vary by locale. Also, historically, I know pattern matching software works well when the content to be filtered is relatively static, like malware. Pattern matching works less well with images, audio, and human-generated text. As an engineer, I would want a more thorough description of your filtering strategies to understand why your app might work where others have failed. Real-world false-positive and false-negative rates would be key if I were a parent. Any LLM integration would also need to be detailed, to understand where a child's data might be shipped for analysis.
Thanks in advance for your time!
Best regards, Eva Bouchard
Thanks, -Brian