Launched this week
Bluerails Discovery
The rails AI agents use to find and pay you
1.2K followers
The rails AI agents use to find and pay you
1.2K followers
Most "AI visibility" tools stop at telling you if AI mentions your brand. Bluerails goes further. We make you discoverable to AI agents and ready to get paid by them, on the rails we already run for marketplaces. What stands out: • Discovery: a peer-reviewed AI-visibility score from 400 samples, not a one-off guess. Free, no signup. • Agent-ready checkout + global settlement • Compliance built in Try your free Discovery report today; agent payments roll out next.
Bluerails Discovery
Hi everyone, I'm Jens, co-founder of Bluerails. 👋🏾
I've spent my whole career watching how the internet decides who wins.
At GetYourGuide (2019 to 2021) I lived inside a textbook Web2 marketplace: aggregate supply, aggregate demand, match them, take a cut. It worked because the internet rewarded whoever owned the funnel.
So, at Passionfroot I built for that same world: software that gave creators their own storefronts. The market corrected us fast. Creators didn't want another storefront, they wanted demand. We pivoted into a marketplace and brought it to them.
Along the way I noticed something the playbook didn't predict: creators around the world were already asking to just get paid, as cheaply as possible. My first glimpse of where money was heading.
In 2025, I started Bluerails to build those rails for global companies and marketplaces. But the deeper we went, the more the ground shifted under the whole model.
The problem: discovery is moving into the AI layer!
Nearly a billion people a week now ask ChatGPT what to buy, and increasingly the AI buys it for them.
OpenAI, Google, Stripe, Mastercard and Coinbase are all racing to build agent led checkout right now.
The new top of funnel isn't ads. It's being discoverable and transactable by AI agents.
And to be transactable, you need a checkout that humans and agents can both use, one that speaks FIAT and stablecoins natively, because agents transact globally, instantly, around the clock, in amounts and ways cards were never built for.
The solution: that's Bluerails, the checkout that brings companies into the age of agentic commerce.
One integration, and your business is ready for both the customer and the agent buying on their behalf, in dollars or stablecoins.
What makes us different:
Most tools in this space stop at telling you how often a chatbot mentions you. We don't just make you findable, we make you buyable. Discovery now, agent commerce next. No intermediaries, no commission.
What you can do today:
Agent Score: scan any URL and get an instant agent readiness score. See exactly how discoverable and payable your site is to AI agents.
Instant Fix: get your llms.txt and a schema fix so you can make your site agent bookable in minutes.
Agent Analytics: measure real agent traffic hitting your site. Understand which AI agents are visiting, what they're trying to do, and how much revenue you're leaving on the table.
Who it's for:
Developers and product teams running sites with digital inventory. Content publishers, hotels, SaaS tools, anyone who wants to get discovered and paid by AI agents before their competitors do.
🎁 Special offer for the PH community: one free month.
We'd love your feedback, especially if you're building agents that need to move money. Drop a comment or reach me at jens@bluerails.com.
Huge thanks to @benlnfor hunting us, and to the PH community for the support. Let's make agentic commerce mainstream.
Jens
Zeno – AI Knowledge Assistant
@benln @j_mannanal super cool what you are building, agents are going to be what moves the economy quite soon, so it makes sense!
Bluerails Discovery
@benln @cderinbogaz Yes, for sure! Just a matter of time, and we'll be there 😊!
Bluerails Discovery
@cderinbogaz thanks for the support
@benln @j_mannanal Congrats ,quick question: for teams just starting to prepare for agentic commerce, what are the top 3 practical changes you’d recommend they make to their product pages in the next 30 days to move their Agent Score meaningfully?
Bluerails Discovery
@benln @swati_paliwal Try it out and see what our report tells you ;) If you want a deep-dive, we can set up a call!
Bluerails Discovery
@swati_paliwal there's no silver bullet for this. It highly depends on your product vertical, market segment, geography among other factors. Happy to schedule a deep-dive session with targeted feedback and a roadmap
With a View
@benln @j_mannanal congratulations on the launch!
Bluerails Discovery
Thanks a lot Darshan! 😊
Bluerails Discovery
@benln @weirdowizard Thanks a lot, Darshan!
@benln @j_mannanal Payment routing for AI agents is such a specific problem space. Are most users discovering you through the AI tooling ecosystem, or did monetization for agents come first in your thinking?
Bluerails Discovery
@benln @clquek Great question. We have a payments background and believe that the future of payments is agent-first. Thinking through it more, we have identified a few industries that will inherently adopt agentic payments earlier due to the shift in discovery.
Bluerails Discovery
@clquek A lot of user behaviour has already shifted to AI agents. People are planning their itineraries on Agents now. Our aim is to close the entire lifecycle within the same context window
@j_mannanal Many congratulations on the launch, Jens, Ashwin and Gurveen! :)
I’ve known Jens since the Passionfroot days, and when I first heard about BlueRails, I was immediately intrigued.
A lot of AI visibility tools stop at telling you whether you show up, but that’s only half the story. Visibility doesn’t pay the bills; transacting does. That’s exactly why Bluerails feels so important... it’s not just about being found by AI, it’s about becoming a business AI agents can actually buy from. This feels like a real step toward the future of customer discovery and commerce.
Bluerails Discover is super exciting. I can't wait to see how the other modules in the product unfold.
Bluerails Discovery
Thank you@rohanrecommends ! Always great to have your support 😊
Bluerails Discovery
@rohanrecommends, thanks! And spot on. I think we can barely fathom how payments will change in the near future.
Bluerails Discovery
@rohanrecommends Thanks for the support
Foyer
Most "get discovered by AI" pitches boil down to structured data and a sitemap. The payment layer is what makes this different, and also where I'd want to understand the mechanics better. When an agent "pays" you through Bluerails, what's actually happening: is there a wallet layer, a per-query micropayment, a subscription the agent operator sets up in advance? And on the discovery side, curious whether you're building a proprietary index that agents query directly or whether you're influencing how existing models surface your content through retrieval.
Bluerails Discovery
Hi @fberrez1 its true about the structured data and a sitemap, but depending on the vertical you're in different types of content and backlinks are also important.
You asked a very incisive question about Agentic payments, the answer is two out of the three you mentioned:
1. A wallet-layer: This allows agents to actually withdraw/deposit funds and make payments and bookings. This is the main payment layer that we are using in the hospitality space.
2. Per-query micropayments: We support the x402 and MPP protocols that allow us to do micropayments. We have partnered with AllUnity to enable these micropayments for publishers/newsletters https://www.linkedin.com/feed/update/urn:li:activity:7473648168367349760/
Bluerails Discovery
@fberrez1 @ashwin_kumar46 Exactly the right split. Our view: discovery without execution is just SEO for agents.
We are not betting on a closed index replacing LLM retrieval. We make merchants machine readable where agents already look, then add the execution layer: wallet based bookings for commerce, and micropayments where content or API access needs per request settlement.
The hard part is connecting intent to a completed transaction.
The 'discoverable to AI agents' half is the sleeper here, and underrated in most of the AI-visibility conversation. Everyone's still optimizing for human SEO; almost nobody's asked how an agent acting for a user actually PICKS which business to transact with. I build an agent that makes calls and bookings for people, and that selection step is the whole ballgame — today it basically inherits search results.
So the sharp question: once real money routes through a visibility score, you've created the strongest incentive in the world to game it — the same way SEO got gamed the moment it started moving rankings. What keeps the peer-reviewed score trustworthy when it's deciding where agent dollars flow? Is the 400-sample peer review the anti-gaming moat, or is there a verifiable fulfillment/settlement signal underneath it? That trust layer feels like the actual product.
Congrats on the launch — this is a real frontier.
Bluerails Discovery
@getosmo great observation, but the 400-sample peer review kills noise. It's not an anti-gaming moat. Our sampling and calculation methodology kills variance and makes the score reproducible.
The anti-gaming layer is exactly what you pointed at. You can fake what an LLM says about you: content, citations; the same surface SEO gamed. You can't fake a settled, fulfilled transaction without actually delivering. Because we're the rail, the score can be anchored to that behavioral ground truth: did it transact, settle, get fulfilled, what's the dispute/chargeback record? That's the Goodhart-resistant signal and that trust layer is the actual product.
Visibility is the leading indicator; settlement is the arbiter.
@ashwin_kumar46 That's the answer — behavioral ground truth (did it settle/fulfill, dispute record) is the only Goodhart-resistant anchor, and being the rail is what lets you actually see it. You can't fake a fulfilled transaction. Convinced.
The follow-up that falls out of it: cold start. The moment the score is anchored to transaction history, a brand-new honest provider has a thin record — but the score is what gates their discovery in the first place. So new entrants either get frozen out (rich-get-richer) or you need a provisional-trust on-ramp, which is exactly the surface gaming would attack. From where I sit (an agent picking who to transact with for a user), I'd skip the unproven provider every time — safe for my user, brutal for a great new business with no history.
How are you thinking about bootstrapping day-one providers without reopening the gameable surface? Feels like the hard part of being the rail.
Bluerails Discovery
@getosmo depending on the vertical, its definitely going to take some time for a day-one provider to become discoverable and then to become trustable. We offer a toolbox and our own expertise to help these providers stand out and serve agents coming to the website with a clear intent
Bluerails Discovery
@getosmo Exactly. The sequence matters here.
We do not start by routing money through a visibility score. We start by making providers legible to agents: verified supply, clear capabilities, content depth and reproducible visibility tests.
Once agent demand is real, fulfillment and settlement become the trust anchor. Visibility is the leading indicator.
Interesting that you’re treating AI visibility as a distribution problem, not just a mention-tracking problem.
The hard part I’d expect is attribution: which agent actually visited, what page/action led to a lead, and whether that became paid intent vs crawler noise.
Curious what signal you trust most today when deciding “an AI agent found us and this is worth optimizing for”?
Bluerails Discovery
@jaemin_song the attribution is indeed a hard problem. But we don't try solve it by scouring logs. That's the crawler-noise trap you're describing. We solve it one layer up: at the rails, a real agent has to present a verifiable identity (Web Bot Auth / Visa Trusted Agent Protocol / ERC-8004) and a signed authorization mandate (AP2 for example) to transact.
Bluerails Discovery
@jaemin_song @ashwin_kumar46 Exactly. Logs are useful, but they mostly tell you something crawled you, not that an agent chose you.
Today we trust the combination of reproducible visibility tests, identifiable agent traffic where available, and downstream lead quality. Once agents actually transact, signed identity and authorization become the clean attribution layer.
So the sequence is: visibility first, intent second, rails once the market is ready.
400 samples for a single visibility score is the detail worth understanding better, what's actually being sampled, 400 different queries against different LLMs, 400 runs of the same query to measure variance, or something else? "peer-reviewed" and "not a one-off guess" implies you're addressing the real problem with AI visibility scoring (huge run-to-run variance for the same prompt), curious what the methodology actually looks like under the hood
Bluerails Discovery
@ansari_adin We've broken down our methodology here https://discovery.bluerails.com/methodology. We also have proprietary weights per vertical
@ashwin_kumar46 Will check that out. Quick one before I do, are the proprietary weights per vertical something you derived from observed variance patterns in each industry, or more just a tuning knob you adjusted based on customer feedback over time?
Bluerails Discovery
@ashwin_kumar46 @ansari_adin Good question. It is not a static tuning knob.
The weights are based on what actually drives agent selection in a vertical, then calibrated against repeated runs, variance patterns and observed outcomes. A hotel, a publisher and a SaaS tool should not be scored with the same signal mix.
We keep the methodology transparent, but the exact weights private because that is where gaming would start.
The architecture question I keep coming back to is what "the rails" actually means technically. Is this a shared API layer that multiple agents connect to, or is each deployment its own isolated setup? That distinction matters a lot for how you'd debug payment failures or audit transaction logs.
Have you thought about extending this beyond payments to other agent-to-agent transactions?
Bluerails Discovery
@demi_tan great questions.
Regarding "the rails", its highly dependent on the ICP. We are currently working with hotels and publishers, the rails differ greatly.
For Hotels its the implementation of an Agentic Commerce Protocol in front of their existing rail (hello UCP) in addition to KYA and anti-fraud capabilities. Eventually it makes sense to replace the outdated PSP/APM integrations for the Agentic age.
For Publishers we are mostly building over the x402 and MPP protocols to support micro-transactions
Regarding A2A transactions: we have working demos for this, but there simply isn't enough traction here to push this into the market yet. We're focusing on enabling Agentic commerce on existing Fintech systems as a first step
Bluerails Discovery
@demi_tan @ashwin_kumar46 This is exactly how we think about it: not one monolithic rail, but also not fully bespoke deployments.
The shared layer is identity, authorization, observability and auditability. The vertical layer is the adapter into the systems that already exist, like hotel booking/payment flows or publisher micropayments.
So the goal is not to rip out every existing stack on day one. It is to make those stacks agent ready first, then let deeper A2A transactions emerge where there is real demand.
LayerProof
Optimizing for AI agent discovery is such a sharp and relevant angle right now, very interested. But how often does the Discovery report update its data to reflect changes or new optimizations a business makes? Excited to see where you take this! 🙌
Bluerails Discovery
@creativewjordyn The report can be generated every month and that's also what we suggest to our customers. Changes are visibly changing the performance after a few weeks. Hence, a monthly rhythm is good!
Bluerails Discovery
@creativewjordyn Depending on the space you operate in there are multiple things you can do to nudge the score upwards month over month. Happy to schedule a deep-dive session