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Hi HN, I’m Alberto. I co-founded Didit (https://didit.me) with my identical twin brother Alejandro. We are building a unified identity layer—a single integration that handles KYC, AML, biometrics, authentication, and fraud prevention globally. Here’s a demo: https://www.youtube.com/watch?v=eTdcg7JCc4M&t=7s.

Being identical twins, we’ve spent our whole lives dealing with identity confusion, so it is a bit of irony that we ended up building a company to solve it for the internet.

Growing up in Barcelona, we spent years working on products where identity issues were a massive pain. We eventually realized that for most engineering teams, "global identity" is a fiction—in reality it is a fragmented mess. You end up stitching together one provider for US driver's licenses, another for NFC chip extraction in Europe, a third for AML screening, a fourth for government database validation in Brazil, a fifth for liveness detection on low-end Android devices, and yet another for biometric authentication and age estimation. Orchestrating these into a cohesive flow while adapting to localized regulations like GDPR or CCPA is a nightmare that makes no sense for most teams to be working on.

When we looked at the existing "enterprise" solutions, we were baffled. Most require a three-week sales cycle just to see a single page of documentation. Pricing is hidden behind "Contact Us" buttons, and the products themselves are often bloated legacy systems with high latency and abysmal accuracy.

We also noticed a recurring pattern: these tools are frequently optimized only for the latest iOS hardware, performing poorly on the mid-range or older Android devices that make up a huge percentage of the market. This results in a "leaky" funnel where legitimate users drop off due to technical friction and fraud goes undetected because data points are spread across disparate systems. Also, these systems are expensive, often requiring massive annual commits that price out early-stage startups.

We wanted to build a system that is accessible to everyone—a tool that works like Stripe for identity, where you can get a sandbox key in thirty seconds and start running real verifications with world-class UX and transparent pricing.

To solve this, we took the "delusional" path of full vertical integration. Rather than just wrapping existing APIs, we built our own ID verification and biometric AI models—from classification and fraud detection to OCR models for almost every language. This vertical integration is fundamental to how we handle user data. Because we own the entire stack, we control the flow of sensitive information from end-to-end. Your users' data doesn't get bounced around through a chain of third-party black boxes or regional middle-men. This allows us to provide a level of security and privacy that is impossible when you are just an orchestration layer for other people's APIs.

We believe that identity verification is one of the most critical problems on the internet, and must be solved correctly and ethically. Many people are rightfully skeptical, especially given recent news about projects that have turned identity into a tool for mass data collection or surveillance. We don’t do anything of the sort, but we also don’t want to be coerced in the future, so we facilitate data minimization on the customer side. Instead of a business asking for a full ID scan, we allow them to simply verify a specific attribute—like "is this person over 18?"—without ever seeing the document itself. Our goal is to move the industry away from data hoarding and toward zero knowledge, or at least minimal knowledge, verification.

The result of our all-in-one approach is a platform that increases onboarding rates while lowering identity costs. We’ve focused on building a high-confidence automated loop that reduces the need for manual review by up to 90%, catching sophisticated deepfakes and spoofing attempts that standard vision models miss. Our SDK is optimized for low bandwidth connections, ensuring it works on spotty 3G networks where legacy providers usually fail.

We are fully live, and you can jump into the dashboard at https://business.didit.me to see the workflow orchestration immediately. Our pricing is transparent and success-based; we don’t believe in hiding costs behind a sales call.

We’re here all day to answer any question—whether it’s about how we handle NFC verification, our approach to deepfake detection, the general ethics behind biometric data retention, or how we think about the future of identity. We’d love your brutal HN feedback on our APIs, platform, and integration flow!

I was frustrated with photo sharing sites. Apple's iCloud shared albums take 20+ seconds to load, and everything else comes with ads, cumbersome UIs, or social media distractions. I just want to share photos with friends and family: fast, mobile-friendly, distraction-free.

So I built DD Photos. You export photos from whatever you already use (Lightroom, Apple Photos, etc.) into folders, run `photogen` (a Go CLI) to resize them to WebP and generate JSON indexes, then deploy the SvelteKit static site anywhere that serves files. Apache, S3, whatever. No server-side code, no database.

Built over several weeks with heavy use of Claude Code, which I found genuinely useful for this kind of full-stack project spanning Go, SvelteKit/TypeScript, Apache config, Docker, and Playwright tests. Happy to discuss that experience too.

Live example: https://photos.donohoe.info Repo: https://github.com/dougdonohoe/ddphotos