Launching today
Wingbits AI
AI agents for real-time aircraft monitoring and alerts
225 followers
AI agents for real-time aircraft monitoring and alerts
225 followers
Create agents that monitor airspace activity 24/7 - military aircraft in a region, private or government jets, a GPS-jamming spike, or a travelling friend or family member - and get alerts the moment something relevant happens. Or just ask anything about what's flying right now. Powered by our own independent network of 5,600+ antennas across 120 countries. No code, no data engineering, no terabytes to store.
Real-time ADS-B data processing at scale is genuinely hard. The fan-out problem for alert subscriptions when flight state changes happen fast is nontrivial. We've wrestled with similar event-driven architectures for customer health signals where latency matters. Are you processing raw Mode S data directly or using a provider like ADS-B Exchange? How do you handle alert deduplication when a flight triggers multiple geofence conditions simultaneously?
Wingbits AI
@anand_thakkar1 we know the pain! Before wingbits.ai we built wingbits.com, a global network of stations collecting data from around the world (check the map). One of our main products is a real-time stream that ingests 3TB of data daily and outputs clean, processed events to our customers with under 1s latency. Low latency is critical for some of our aviation customers, and that’s why we want control over the full stack.
On your second question, that’s something we’re still working on. During the beta we included some basic checks, but it’s an area we’re actively improving.
What did you land on for your fan-out problem? Always keen to compare notes.
Wingbits AI
Hey Product Hunt 👋
I'm Alex, co-founder of Wingbits.
For the last two years we've built a completely new flight tracking network: 6000 antennas across 120 countries, generating terabytes of data daily, with Spire Global and Korean Air as customers. Until now, gaining insights from this data required a data science team. Now we're launching Wingbits.ai so everyone else can easily get answers too.
It's made for reporters, prediction markets, competitive analysts, route planners, aviation enthusiasts. Anyone can extract geopolitical or operational insights by just asking in plain English.
No code, no data processing, no infrastructure.
A few things you can do today:
Ask "where is Air Force One right now?" and get a live map link to track it
"Which private jets visited Davos last weekend?" or "Mar-a-Lago last Saturday?"
Spin up agents that send alerts to Slack, email, Telegram, or Teams the moment something matches your criteria
Compare GPS jamming events across regions, or
Get scheduled reports or analysis on things like competitor routes
PH community gets a free tier, or 1 month of Pro free with code HUNTERS.
Let me know - what's one thing you've always wanted to know about aviation, but never had the tools for?
— Alex
The alert agents are the most interesting part for me. Most people don't need all the raw flight data, they need to know when something unusual happens. How do you filter signal from noise when tracking things lie route changes or GPS jamming events?
Wingbits AI
Thanks @ada_johnsen! It depends on the use case, of course, but I agree, the alerts are one of the most powerful features. Route changes are actually easy to detect but hard to interpret, since a deviation can happen for many reasons: disruptions, weather, or just unusual events. That's why we're working on integrating other data sources, like NOTAMs and weather alerts, to add the context that tells you whether a change actually matters.
GPS jamming is more straightforward, since the data is tagged with quality and certainty parameters. So we can check whether a reading is highly uncertain (as reported by the aircraft) and whether it's in an area known to be affected, like near conflict zones.
Wingbits AI
@ada_johnsen building on what Alex said, the context layer is a part we're quite excited about. Raw deviation alerts are easy to generate but exhausting to act on, because most flight path changes are mundane (weather, ATC reroutes). What we keep hearing from the newsrooms and analysts testing the platform is that they want fewer, smarter alerts that come pre-contextualised, not more raw data.
On GPS jamming specifically - the daily aggregated view at wingbits.com/gps-jamming has been a really useful reference point for journalists covering the Baltic and Middle East. This was even covered in The Independent: https://www.independent.co.uk/news/world/middle-east/gps-jamming-spoofing-iran-us-israel-war-b2938167.html
Curious what you'd want to monitor - maybe we can spin up a test agent for whatever's interesting to you?
about the alert latency. ADS-B data has inherent delays depending on antenna coverage density and how quickly data gets aggregated. for something like a GPS jamming spike where timing actually matters, what's the realistic gap between an event happening and an alert reaching the user. and does coverage quality vary enough by region that some alerts are significantly more reliable than others
Wingbits AI
Thanks, that's a really good question @ansari_adin! Aside from station coverage, the data depends on how many flights are in the region at the time, since it's sourced directly from aircraft. We aggregate hourly for that reason, but the dataset can still be noisy (you can see the daily aggregated data on wingbits.com/gps-jamming)
For alerts, we use a rolling 24h window, which should fire fairly quickly if there's a significant spike in well-trafficked areas like the UAE. We're also working on pulling in data from the stations themselves, since they all have GPS and are affected by jamming too.
@lungu Real-time monitoring is one of the cleaner use cases for agents because the signal and response window are clear. The hard part is making sure alerts stay useful instead of becoming another stream of noise.
Wingbits AI
@alpertayfurr true! Alert fatigue can be a real problem. We let users set both the cadence of the evaluation and the time windows for the data sample, which helps a lot if configured right. The agents also have access to the history of alerts and can decide whether enough has changed to be worth flagging.
What kind of activity would you want to keep an eye on?
Thanks a lot for the feedback!
The alerting aspects is what stands out most. Knowing when something important happens is often more valuable than constantly watching dashboards.
Wingbits AI
@eric_donovan couldn't agree more! The agent watches the airspace so you don’t have to sit on a dashboard, and it only pulls you in when something actually matters. One thing we might not have communicated well enough is that the agents can also create reports, not just alerts. For example, you can setup one that at the end of the day, sends a report on the utilization of the local police helicopter.
Is there anything you'd like to be alerted about?
Thanks a lot for the feedback!
Wingbits AI
@eric_donovan Yup thats one of our key value preposition, especially for media segment and journalists
Building AI agents on top of live ADS-B data feeds is genuinely tricky since the message stream is noisy with duplicate transponder IDs and position errors. We've worked with high-frequency event streams in our own infrastructure and know how hard accurate state reconciliation can get. What's your approach to deduplicating transponder messages and handling geofence evaluation latency when multiple flights trigger alerts simultaneously?