Our Story
I'm the co-founder of Zipy.ai and for the past 3 years, we have built a platform that helps teams solve customer frustrations through session replays, user behavior analytics, and error monitoring. Today, I'm proud to announce the launch of our mobile support for Flutter and React Native, both on iOS and Android. Java/Kotlin is soon to follow.
The Problem
In this journey over the last few years, we have interacted with hundreds of mobile developers and many mobile founders, who were solely depending on Firebase to catch their crashes, but there was one unsolved problem - they weren't able to understand the user side of the story which caused these crashes, ANRs or freezes. The major ask each of them had was the ability to magically replay user actions on their mobile app.
With this launch, you'd not only be able to do that, but also catch and prioritize their problems with our AI-powered "Oopsie bugs".
The Solution
Debug mobile app issues instantly with AI bug detection. Supercharge your Flutter and React Native debugging with AI-powered mobile session replays: https://www.zipy.ai/for-mobile
▶ Replay mobile user sessions in real-time
Detect UI errors with "Oopsie Bugs"
AI-generated summaries & repro steps
Catch ANRs, crashes with logs & traces
Firebase Crashlytics Integration
looks like a beast. With impressive CPU and GPU gains, it's closing the gap with Apple while outpacing Google's Tensor G4 by a massive 63%. Multi-core performance is where it really shines, delivering a 40% boost over the Snapdragon 8 Gen 3 and showcasing serious gaming potential with up to 34% faster graphics. If these benchmarks hold up, the next-gen Android smartphones might finally outpace Apple in performance. Can’t wait to see how this translates into real-world use!
It's really impressive to see how determination and a bit of technical know-how can overcome such blatant profiteering by some companies. The effort and ingenuity put into fixing the system rather than just paying for an overpriced replacement are commendable. It's a clear reminder that proprietary smart systems can sometimes backfire, pushing customers to seek alternative solutions or even become DIY experts out of necessity!
Like some of the commenters, I've been thinking about the growing frustration with these kinds of business practices. It really makes you wonder about the balance between smart technology's convenience and the long-term costs they can impose.
What do you think would be the most effective way to encourage companies to offer more consumer-friendly solutions, especially for minor issues like this? Should there be stronger regulations, or is there a market opportunity for more open-source, user-modifiable systems?
your point about "chronus" or auto recoil adjust cheats is a perfect example of how cheats evolve to bypass detection. By modifying controller inputs at the hardware level, it’s nearly impossible for traditional anti-cheat software to identify such exploits. It shows that as long as there is an incentive, people will find creative ways to gain an advantage, often blurring the line between legitimate skill and unfair advantage.
I think moving forward, a hybrid approach is essential—one that leverages both server-side logic to prevent information leaks and robust client-side monitoring that can detect anomalous behavior patterns. Perhaps more sophisticated machine learning models that analyze player behavior in real-time could help in distinguishing between legitimate skill and enhanced performance due to cheats. It's a constantly evolving battle, and staying one step ahead is always going to be a challenge.
Would love to hear more thoughts on how to effectively balance these aspects without compromising the player experience!
@Animats, you’re spot on about the two main issues—visibility hacks and aimbots. The concept of hiding enemy positions server-side through occlusion culling does present a performance challenge, but it’s essential to balance between ensuring fair play and maintaining server efficiency. And you're right; the rise of external programs that can interpret video output makes preventing aimbots significantly harder.
Yes piyushtechsavy - We are GDPR and SOC2 compliant - and we don't capture any sentivite PII data from the users. You can also control what UI elements to be masked in the sessions that are created. And RB2B provides leads only in the US region, hence they don't need to be GDPR compliant - so if you're using Zipy+RB2B in the US - what we are offering is totally safe and legal.
If you are in the EU, RB2B doesnt give leads - so there's no question of privacy there. And Zipy anonymously captures session recordings and is GDPR compliant in EU region. Please refer to our documentation and lemme know if you have any questions: https://docs.zipy.ai/getting-started/sensitive-user-data
Thanks vishalk_3. This is an integration we built internally to make sure our marketing team can qualify and follow up with leads based on their behavior and intent on the website. Looking at the immense potential here, we decided to make it free and public for other companies to use. Pls share your feedback once you use it.
Hope you like it. Lemme know if this is useful to your marketing/product teams in any way. Your feedback would tell us if we can spend more time here, on this offering. :)
Thanks for your insights - what tools do you use for tracking all this? I started used RB2B plugin in slack which identifies linkedin and email ids of website visitors. And I have my own tool Zipy.ai which captures user activity session recordings on the website. So we map both of them to identify users and see what they're doing. Planning to build an integration of both the tools soon. What is the tool stack that you use?
Thanks for sharing those tools! They definitely cover a lot of ground for tracking and analyzing user behavior. I'm curious—how do you balance between PLG and SLG motions when it comes to choosing the right metrics? Do you find that certain tools work better for one approach over the other?
Do you follow the inbound-led outbound approach suggested by RB2B - reason why I'm asking is we did a powerful integration with RB2B + Zipy - to get linkedins/emails of website visitors into slack, and also map them with the visitor user sessions. Been one of the greatest integrations till date - immense insights.
That sounds like a powerful setup! Being able to track individual visitor journeys and compare conversion rates across different channels must provide some great insights. How do you typically act on the data you gather? For example, do you find yourself making specific UX adjustments or marketing decisions based on what you see in those visitor journeys and segment comparisons?
Totally agree with you on the native differences—it can be a bit of a headache, especially when dealing with things like BLE and permissions. Testing on each OS is definitely key. How do you usually manage the debugging process when you run into platform-specific issues? Do you rely on any particular tools or strategies to streamline that?
I have given it a try. For technical errors, exceptions it is fine. But if you have to narrow down on to user experience challenges in the user flows - it's difficult to do that. How do you manage those? Also, crashes is hard on sentry - we use crashlytics for that.
It's fascinating to learn that bacteria can thrive in such an extreme environment, but it also raises concerns about potential health risks, especially in shared spaces where microwave cleaning is often neglected.
How often do you think microwaves should be cleaned to effectively minimize bacterial growth, and what cleaning methods do you find most effective in ensuring they stay hygienic?
Awesome. I checked it out and forwarded it to my team. However their feedback back that since we already use chargebee for subscription management, this might add little value for our usecase. This requires the management of when to start the cycle, when to subtract credits, how much of credits to subtract at our end itself. Added info if required to be extracted will need to be passed on via apis - which might add more work to implement this. Thought i'll share the feedback so that you can think in this direction in the future. All the best!
congrats man. This is cool. Does the work on mobile apps too? We are coming up with a mobile app where users have to buy AI credits as add-ons - and we were building out own credit sysyem. How can this help?
What are the key advantages and potential challenges of utilizing GPU acceleration in Flutter for cross-platform app development, particularly in terms of performance and resource management?