Explore Problems

Developers building AI agents need real-time social data (Twitter, LinkedIn, Reddit, YouTube) but direct scraping causes immediate account bans and official APIs are too expensive or restrictive.

Developers building multi-step AI-powered backends waste significant engineering time writing regex and error handlers because LLMs inject markdown into JSON payloads or hallucinate structured outputs.

A collector reports a disputed debt to credit bureaus without ever supplying the documentation the consumer requested to verify it, leaving the dispute unresolved on the credit file.

Mobile developers abandon automated testing because tools like Appium and Espresso rely on fragile element selectors that break whenever UI changes, making test maintenance cost exceed value.

Privacy-conscious developers and enterprises cannot use mainstream AI coding tools (Copilot, Cursor) without their proprietary code leaving the local machine, with no viable fully-local alternative.

Stripe terminates long-standing accounts based on incorrect risk assessments. Legitimate businesses like ad agencies serving Fortune 500 clients get flagged and shut down without recourse.

Shopify templates and third-party extensions glitch unexpectedly with no support available. Unreliable extensions create business risk for merchants.

Salesforce CRM UI continues to fall short despite being widely adopted. User experience is the primary critique for this major platform.

Intuit copies features from integration partners, raises subscription prices, and justifies hikes with buggy features that should still be in beta.

Quantum computing hardware costs millions and access is gated by the companies who own machines. A distributed network could democratize access.

Polymarket web platform is nearly unusable on mobile, lacks price alerts, trader following, and auto-redemption when positions resolve — gaps that drove 600 organic users to a third-party tool.

Sales teams want to find leads by describing them in plain language rather than building complex filters, covering B2B, local, and social contact discovery.

Software buyers cannot reliably verify whether testimonials are authentic, enabling bad actors to publish fabricated social proof on brand-new products with zero real customers.

Enterprises need a model-agnostic, self-hostable multi-agent AI platform with SSO, audit trails, approval workflows, and a non-developer UI — existing solutions lack enterprise security controls or create vendor lock-in.

Non-technical product managers spend excessive time manually tracking which PRs block others, chasing completions, and managing dev dependencies without engineering context or adequate tooling.

Non-DevOps founders and indie developers spend weeks just getting an app online, finding current deployment platforms still require significant infrastructure knowledge that shouldn't be necessary.

Founders struggle to develop reliable feedback cycles for new products after the landscape shifted.

iOS users cannot easily connect AI assistants to their Apple Health data while keeping that data on-device and private — existing solutions require sending health data to third-party servers.