Ideas Lab
Real problems people complain about online, pulled every morning and scored out of 100. Build, validate, or skip. How scoring works
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Small businesses need automated accounting but existing solutions are too complex or expensive
Small businesses, especially in emerging markets, struggle with manual bookkeeping and can't afford complex accounting software or professional services.
YC Graveyard4y agoToolFinance
AI-Generated Content Detection for Educators & Publishers
Educators, publishers, and content moderators need a simple tool to detect if text was written by ChatGPT or similar AI models. Existing detectors are unreliable, paywalled, or fragmented across platforms. [Google Search suggestion]
Google Trends6mo agoToolEducationUS
Video creators need better monetization through contextual advertising
Video creators struggle to monetize content effectively, especially with ads that are relevant to specific moments in their videos.
YC Graveyard15y agoToolMedia
Mass block tool for engagement farming accounts on X
X users are annoyed by engagement farming accounts and want a way to mass block them instead of one-by-one.
X8mo agoToolProductivity
App for disguised self-messaging as if from other people
No app exists to let users send messages to themselves that appear as coming from someone else, for sharing random thoughts or self-motivation without it looking self-sent.
X8mo agoToolPsychology
Repositories lack automatic AI-updated documentation for LLM agents
Developers merge PRs but documentation like READMEs isn't updated to reflect changes, forcing LLM agents to scan entire codebases inefficiently instead of quick-reference docs.
X8mo agoToolDev
How much should I pay for the given website.
Project Title: Micro-Task Platform Project Overview Build a web platform where clients can create online tasks and workers can complete them to earn money. Workers submit proof, tasks are verified automatically or manually, and earnings are credited to their wallet. The platform must support crypto withdrawals and an admin management system. User Roles 1. Worker - Create account and login - View available tasks - Complete tasks and submit proof (link or screenshot) - Track earnings and task history - Request withdrawals 2. Client - Create campaigns/tasks - Set reward amount per task - Define number of workers required - Track task completion statistics - Pay for campaigns 3. Admin - Approve or reject task submissions - Manage users - Manage campaigns - Process withdrawals - Monitor platform activity Core Features User System - Registration and login - Email verification - User dashboard - Wallet balance display Task System - Task listing page - Task instructions page - Proof submission (URL or screenshot upload) - Task status tracking (pending / approved / rejected) Verification System - Automatic link validation for tasks when possible - Manual admin approval for complex tasks Wallet System - User balance management - Earnings credited after task approval - Withdrawal request system Payments - Crypto payments (USDT, BTC, ETH) - Admin manual approval for withdrawals Admin Dashboard - View all users - Manage tasks - Approve submissions - Approve withdrawals - Platform analytics Security & Anti-Fraud - Duplicate submission detection - Rate limiting for tasks - IP monitoring for multiple accounts Technical Requirements Frontend Responsive web interface. Backend API based architecture. Database Store users, tasks, submissions, and transactions. Optional Features (Phase 2) - Automated verification via social platform APIs - Referral system - Reputation score for workers - Automated crypto payouts - Real-time notifications
Reddit8mo agoToolDev
outsourced our phone answering to save time and now we're spending more time fixing the notes than we saved
We run a small insurance agency and phones are the biggest time suck in the office. Figured we'd try one of those call answering services to handle the easy stuff while we focus on quotes and renewals. Three weeks in it's a mess. The operators keep mixing up policy numbers and claim numbers in the notes they send us, carrier names are misspelled half the time, and if a client asks anything slightly specific they just transfer the call right back to us. So we're paying for a service that handles maybe 20% of calls on its own and creates cleanup work for the rest. One call really got me. Commercial client called about adding a location to their bop. Notes came back saying "customer wants to add a body shop to their policy." I still don't understand how you get there from what was actually said. Another time someone called about their personal umbrella policy and the only note was "customer has question about umbrella insurance." Zero context, zero details, so we had to call the client back and redo the whole conversation. The frustrating part is the terminology isn't even that complicated once you learn it but these generic services clearly don't train their people on any of it. I'm pulling the plug this week. Been poking around at some of the industry specific options, saw a few names come up like sonant and a couple others that are supposedly trained on insurance calls specifically but honestly at this point I'm skeptical anything that isn't our own staff will get it right. Anyone else dealt with this when trying to automate or outsource something in a specialized field? feels like the generic tools just don't cut it when there's real domain knowledge involved.
Reddit8mo agoToolProductivity
A startup founder loses focus and productivity juggling 5-7 tools for a single project. Existing «all-in-one» platforms don't provide the feel of a unified workspace.
ProblemHunt9mo agoToolProductivity
Fans of paper planners lack an iPad app that would allow importing PDF layout templates and using them as a foundation for digital notes
ProblemHunt10mo agoToolProductivity
Clients struggle to verify the competence and pricing honesty of freelancers when creating websites — there is no AI tool for real-time proposal analysis.
ProblemHunt10mo agoToolFreelance
Problem of access to loans for immigrants in the EU
ProblemHunt1y agoToolImmigration
Problem of managing type 1 diabetes without AI assistance
ProblemHunt1y agoToolAI
Platform to manage and plan artificial reef deployments
Building artificial reefs involves coordination between environmental groups and regulators. A digital tool can assist in planning, tracking locations, and monitoring impacts to streamline ecological projects. [Trending: "artificial reef" with 200+ searches in GB]
Google Trends10h agoToolOtherGB
AI-Powered Video Creation Tool for Non-Experts
People want to create videos quickly using AI without complex editing skills, but existing solutions are expensive, limited, or fragmented. A simple AI tool can enable fast, customizable video production. [Google Search suggestion]
Google Trends10h agoToolAIUS
Tool to monitor and alert local businesses about ATM ram-raid risks
Repeated ram raids on ATMs cause financial loss and insecurity. A digital tool could aggregate police reports, local crime data, and send early warnings to businesses for preventive action. [Trending: "whittlesey atm ram raid police" with 100+ searches in GB]
Google Trends10h agoToolOtherGB
Simplify ICAI Exam Result Tracking and Alerts
Students preparing for the ICAI CA exams need a simple tool to get instant notifications and easy access to their exam results and scorecards, improving their exam follow-up process. [Trending: "icai result sep 2026" with 500+ searches in IN]
Google Trends10h agoToolEducationIN
A decent text-to-image model trained for ~$20K (Apache 2.0 Weights)
My brother and I run a 2-person lab that trains our own generative video models from scratch. The ultimate goal is a set of creative tools that make it easier for anyone to make animation.Video models today are too slow/expensive and lack sufficient controls. Creativity is an iterative process. You make, you tweak, you get better. In our opinion, they're not usable yet for storytelling.When we set out to build Linum v3 (our next video model) earlier this year, the primary goal was to bring the cost envelope of inference down significantly. If our model is fast and cheap, it's the first step (of many) towards useful creative tools.Typically, you see "latent diffusion models". A VAE (Variational Autoencoder) compresses the input data into a smaller "latent space" and the diffusion model learns how to generate within this subspace.Over the past few months, we've been publishing our work on efficient pixel-space diffusion models. These throw away the VAE, having the diffusion model learn a latent-space optimized for its exact task.This serves 3 purposes: 1) Simplify Architecture (no 2-stage model training) 2) Faster Convergence (11x faster convergence vs. our latent diffusion counterpart) 3) Cheaper Inference (4x more aggressive token reduction in attention context-windows, without significant loss in quality)This past month we were pressure testing our latest architecture (Pyramid-JiT) by training a text-to-image model longer than the typical one-off experiment. Specifically, we trained it for ~$20K on 660M samples.We were surprised by the quality of results, so we thought we'd release it as open weights for the community (Apache 2.0). The research itself is already public, on our website.For us, it's a big stepping stone towards cheaper video models, since pretty much all video models start as image models. We like to say these models have to learn nouns before they learn verbs.
Hacker News1d agoToolAI
Rivet (YC W23) – Scale and Orchestrate Agents on S3
Hey HN, this is Nathan and Nicholas from Rivet (https://rivet.dev) – a fast, high-density, and scalable orchestrator for agentic workloads using the actor model. Rather than running a heavyweight sandbox per agent, each agent gets a lightweight actor backed by S3.Actors provide a long-lived process for long agent turns, in-memory state for context, a WebSocket server for multiplayer, durable SQLite storage backed by S3, and hibernation when idle.It's a similar model to Cloudflare Durable Objects, but it’s open source and self-hostable.Here’s a video walkthrough: https://www.youtube.com/watch?v=3Ev6I7DOV9cWhen we went through YC in 2023, we were building infrastructure for multiplayer games like Diep and Krunker. This involved heavily optimizing high-throughput matchmaking, real-time player messages, and blitz scaling. Through that process, we spent a lot of time on workloads where Postgres couldn't keep up with our throughput. We started out by hacking together Lua scripts on top of Redis, but this became too cumbersome to maintain and upgrade. This led us to extend our game server orchestrator to support what we call Rivet Actors today: many lightweight workers with in-memory state and durable storage. By using actors, we were able to serve tens of millions of monthly active users.As agents grew in popularity, it became clear that running agents in sandboxes is inefficient. Sandboxes are expensive, mostly idle, and slow to start. Developers started using actors because they are far more memory efficient (72 KB baseline for actors vs 512 MB for a minimal sandbox) and fast to start (4.9 ms p99 for actors vs 1.7 s p99 for sandboxes).For example, Amp is using Rivet to orchestrate multiplayer agents. They originally tried to build on Cloudflare Durable Objects, but couldn’t launch because of the platform’s limitations and unresponsive support. They migrated to Rivet Actors in a weekend and deploy on-prem. Rivet’s flexible architecture
Hacker News17h agoToolAI
Firenook – Firebase emulators in Rust: 40× faster writes, 10× less RAM
Hi HN, we have been developing with Firebase for a long time, and the only way Firebase developers can build apps without directly costing them is using the official Firebase Emulator Suite.However, the issue with this suite is, it's dependent and running on Java with a old Console UI (not updated in years), that was not built to support tons and millions of data and has pretty bad developer experience. For a long time, we were hitting Out of Memory on even high specs laptop while developing and the worst part is while this happens all the persists data keep getting lost.We were honestly frustrated with this, and thought what if we built the Firebase Emulator Suite the right way, as it always should have been.Introducing Firenook, a faster drop-in replacement for Firebase Emulator Suite for Firebase developers. It's 40x faster writes and needs 10x less RAM to run it. We took the right approach of first building it Rust as a single engine, so that there will be no Java dependencies and built from scratch a new Console UI using modern web stacks.The result is, now we were able to run 2 millions datas loaded to Firenook with only taking around 2GB ram compared to 22GB of the official suite. Things are way faster and rebuilt Console UI gives best developer experience from logging Firebase Functions, to editing Firestore documents in JSON and many more.We developed this throughly for around 2 months now and ran this internally for a month before we decided it's time to release it to public so that other devs can make use of Firenook and also contribute it to make it better.Firenook is still new and I'm sure it misses things. So please try it our on your project and let us if there are any issues.Thank you.
Hacker News21h agoToolDev