AirKaren - AI that fights customer service for you
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AirKaren is the AI that fights customer service for you, completely for free. Tell Karen what went wrong with your flight, and she cites the regulation, files your claim, and chases down what you're owed. Karen will call customer support hotlines, send emails, and fill out forms so you never have to again. We're starting with airlines and expanding to other industries in the coming weeks.
Replies
AirKaren
This is one of those products where the name alone made me click :))
Customer service is exactly the kind of task I don't want AI to summarize for me, I want it to actually do it. finding the right regulation, filling out forms, following up, waiting on hold... that's all busywork. Starting with airlines also makes a lot of sense. almost everyone has a story where they probably should've claimed compensation but gave up because the process wasn't worth the time.
Curious how Karen handles edge cases where airlines reject the claim even though the regulation seems pretty clear. does it keep escalating automatically, or is there a point where a human steps in?
AirKaren
@andrasczeizel Hey Andras! You nailed exactly why we started here: the compensation is almost always owed, but people just give up because the process is pure busywork.
On rejections, we split failures into two buckets. Technical hiccups (a form times out, a page changes, a CAPTCHA) get retried a few times automatically. Karen persists through the mechanical stuff. However, a substantive pushback, meaning that the claim is contested or genuinely gray, doesn't get auto-hammered. It routes to a human review queue. We'd rather have a person build the strongest next move on a disputed claim than have a bot fire off weak auto-appeals that airlines learn to ignore. Fuller autonomous escalation is on the roadmap, but the whole thing falls apart if Karen starts sending stuff that's easy to dismiss.
Thanks for the thoughtful question!!
Superb job! Starting with airlines looks quite smart as EU261 gives the agent an actual statute to cite instead of asking for goodwill right? The phone part is interesting. Airlines push every claim toward their own web forms because forms are where claims stall out. In practice do you guys get further on the hotline than through the official form?
AirKaren
@artstavenka1 Great question! Yes, that's the logic for us – EU261 in particular is nice because the agent can cite the regulation directly (and a deterministic compensation amount) instead of asking for goodwill, which changes the tone of the whole interaction. On hotline vs. form: while we only launched a few days ago, we suspect that the form with repeated escalation and bumping over the phone/email might be the way to go :) Happy to share more details if useful.
AirKaren
Founder here. We recognized that companies intentionally evade paying consumers what they're owed, and we built a tool to address it.
In our beachhead market, airlines, the regulations are clear and concrete, yet 85% of passengers with eligible claims never end up receiving compensation. That gap having the right to a claim vs. actually being able to enforce it – is the whole reason AirKaren exists. Karen does the annoying part: figuring out what you're owed, citing the right rule, writing the claim, and not giving up when the airline stalls.
Would love to know: what's the next industry we should tackle? We're on a mission to help people get the money they're owed, and we'd love for you to be a part of the journey.
Tried it on a delayed flight from last month and Karen actually cited the EU261 regulation and got me a partial refund without me picking up the phone, which is wild. Honestly the most "where has this been" feeling I've had from a new tool in a while.
@nilferejbc Dang that's impressive! I clicked out of curiosity from the name alone but I am pleased to hear how effective AirKaren is.
AirKaren
@nilferejbc This is exactly the story we want to hear. No hold music, no repeating yourself to three different reps, just the regulation doing the work for you. Really glad it came through on the first real case!
Naming an AI that fights airlines "Karen" is the kind of poetic justice I didn't know I needed. Finally, the manager-summoning energy pointed at the people who actually deserve it.
My contribution to the horror archive: once spent 90 minutes on hold with an airline over a delayed bag, got cheerfully disconnected right as a human picked up, and simply... gave up. They won. They always win. The fact that Karen would've just handled that while I did literally anything else is genuinely great. Consider me a fan.
@benln @max_beyer @_jai @emile_labrador
AirKaren
@sharun_kanan The name earns its stripes every time someone tells us a story like this. The customer service process is beyond enraging, but Karen doesn't get tired, doesn't get disconnected, and doesn't give up. Thanks for your support!
I really love the idea because sometimes I only go through half the claim and then I give up. My question is : Has there ever been some company airlines that refused to deal with the claims that AirKaren Made ?
AirKaren
@reda_roqai_chaoui Good question! A lot of the time (specifically over the phone) airlines are hesitant, but normally a little persistence does the trick :)
For AirKaren, how do you decide when the AI should keep pushing a customer service conversation versus handing it back to the user? Since this sits in the AI Agents / workflow automation space, I’m curious if there are guardrails for tone, refunds, account-sensitive details, or cases where a human needs to approve the next message.
AirKaren
@mia_qiao Hey Mia! Great question – this is honestly the core design decision for us.
The short version: Karen is deliberately biased toward handing back to a human whenever there's ambiguity, not toward pushing. Every claim runs through an eligibility engine before Karen sends anything, and it lands on one of three verdicts:
Clear-cut → Karen files it autonomously
Ambiguous → routed to a human review queue before anything goes out
Clearly not covered → we stop and tell the user exactly why
"Ambiguous" is intentionally broad. If we can't independently verify the delay, if it's a cancellation where the notice period matters, or if the airline might invoke "extraordinary circumstances" (weather, ATC, security), a human looks before Karen acts. We never auto-reject a passenger in a gray area – the airline carries the burden of proof, not the user.
On the sensitive-details side: Karen doesn't free-form negotiate today. It works through structured, law-grounded filings that cite the specific articles they rely on, which keeps it on script. Happy to go deeper on any of these.
Finally something that might actually get me a refund without spending two hours on hold. Loved that Karen cited the actual regulation back to me, felt like she knew the playbook better than the airline agents.
AirKaren
@ikratekmen32688 That means so much to us! This is exactly why we built Karen. Airlines (and big corporations in general) bank on consumers both not having the knowledge and the bandwidth to cite the actual rules. Glad she held her own!
"Completely free" is the part I keep re-reading. Calling hotlines, filing claims, and escalating on someone's behalf isn't cheap to run, especially at any real volume, so I'm trying to figure out where the business actually makes money. Is it a cut of the compensation once you get paid, or is this VC-funded and free-for-now while you build usage data? Asking because if the model is a percentage of what you recover, that's a completely reasonable business, but it also means the AI has an incentive to push claims as high as possible rather than just what's fair, and I'd want to know that upfront before handing it my flight details.
AirKaren
@galdayan Fair question, and glad you're asking it upfront. Right now, we're free for users — we're VC-backed and using this stage to prove out the model and build usage data before we're out of beta. Once we exit beta, we'll move to a success fee (a cut of what we recover), so no cost to you, and we'll be transparent about that fee when it kicks in.
On the incentive concern: many claim values are fixed statutory figures based on specifics of the actual incident, not negotiable ranges, so there's no lever for the AI to "push higher." Karen's job is to prove eligibility and build the case, not to negotiate a number. For the ones that are more variable, we estimate the amount owed under various regulations before we fight the claim and aim for that specific number. Hope this makes sense! Something we've put a lot of thought into.