AirKaren
AI that fights customer service for you
324 followers
AI that fights customer service for you
324 followers
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.
Free
Launch Team / Built With
EneyProactive AI for Mac. Free test, 20,000 credits.
Promoted
AirKaren
@max_beyer I got stranded in Burlington Vermont for 12 hours because my Greyhound left 30 mins early, @karen pls fix
AirKaren
@max_beyer @dimitrijeg0404 Overhauling the roadmap right now
An AI whose whole job is to out-patience a company betting on your exhaustion, that's the right fight :)
My honest question is language. It looks English/US-first for now (airline hotlines, forms), but the people who most need someone to fight for them are often the least comfortable arguing in a second language, a French passenger stuck with a Spanish carrier, an immigrant on hold with a local telecom. Does Karen already run a claim end to end in the customer's own language (calling and emailing in French, Spanish, and so on), or is multilingual on the roadmap? That's the line between a neat US convenience tool and something genuinely leveling.
Congrats on the launch, and rooting for the expansion beyond flights!
AirKaren
@keirodev Thank you for the support Kevin! Good question :)
Multilingual is absolutely on the roadmap and, to some extent, we can handle it now. The good news is that most airlines (particularly larger carriers) will allow us to talk to them in English. For other dispute types, however, that's absolutely something we'll build in!
Dial
"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.
Treatings
After Delta 1) didn't put my daughter's stroller on the right plane this weekend and 2) delivered it three days later with holes in it, you've got a submission coming....Karen, do your thing and don't be shy!
AirKaren
@howillia Yessir! Please let me know if you have any questions – happy to solve this claim.
YourSitee
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.
Tencent RTC
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.