ZeroScam's answer

Most scam detection tools rely on URL blacklists or known malicious domains. ZeroScam analyzes the persuasion patterns within the message itself — urgency signals, impersonation cues, and authority mimicry — the tactics scammers use regardless of domain or sender.

It also explains why a message looks suspicious, helping users learn to recognize scams over time.

No account required and messages aren’t stored.

TranscriptFetch's answer:

Most short-form video has no caption track to download. TikTok’s auto-captions are opt-in per upload, Instagram never publishes a downloadable track, and many captions on both are burned into the video frames where no parser can read them. TranscriptFetch transcribes the audio when no caption track exists, on the same endpoint, with the same response shape. Your code never branches on which method produced the text. It also covers YouTube, TikTok, Instagram, X and Facebook plus any web page as clean Markdown, so a pipeline spanning several sources is one integration rather than five.

ZeroScam's answer

ZeroScam is simple, private, and works with any message — no account, no installation, and no message retention.

Instead of relying on threat databases or infrastructure signals, ZeroScam looks at the message itself and explains what might make it suspicious.

The goal isn’t just detection, but helping people understand how scams work so they can recognize them more easily next time.

TranscriptFetch's answer:

Three reasons. Coverage: one API key and one response shape across five video platforms and the open web, instead of stitching together a library per platform. Reliability: requests run through rotating infrastructure, so code that works locally keeps working from a server, which is where most open-source approaches break. Billing that matches reality: one credit per successful response, with failed, blocked and empty results never charged. That last point matters on short-form video, where a meaningful share of any batch is music with no speech in it. There is also an MCP server, so AI agents can fetch transcripts as a tool without a custom integration.

ZeroScam's answer

ZeroScam started after my own parents nearly fell for a scam. The message looked completely legitimate — correct language, personal details, even their bank’s logo. AI had made it convincing enough that they almost clicked.

That moment made something clear: modern scams no longer look suspicious. The warning signs people used to rely on are disappearing.

ZeroScam was built as a simple way to double-check suspicious messages before clicking, replying, or sending money — especially for the people we care about most.

TranscriptFetch's answer:

It started with discovering there is no good way to get the text of a video. YouTube’s official Data API will confirm a caption track exists and then refuse to hand it over, because captions.download requires the video owner’s OAuth token. The popular open-source libraries work until you deploy them, at which point platforms start refusing datacenter IPs. And YouTube is the easy case: TikTok and Instagram publish no caption file at all. Every workaround solved one platform, worked locally, and broke in production. TranscriptFetch is the version that handles the failure cases as first-class behaviour rather than edge cases.

ZeroScam's answer

ZeroScam is designed for everyday users who want a quick way to verify suspicious messages.

This includes people receiving unexpected texts or emails, families helping older relatives stay safe online, and small businesses that want to double-check unusual requests.

Anyone who has ever wondered “Is this message a scam?” is part of the audience.

TranscriptFetch's answer:

Developers and technical teams building on video and web content. The common cases are RAG and retrieval pipelines that need video as text, AI agents that need to read a link mid-conversation, content teams repurposing short-form video at scale, and media monitoring and research tools. It is an API first, so the buyer is usually the person writing the integration rather than an end user. The free browser tools exist for one-off transcripts and for evaluating output quality before writing any code.

ZeroScam's answer

ZeroScam is built using modern web technologies and a custom message analysis engine designed to identify common scam patterns while maintaining strict privacy principles.

TranscriptFetch's answer:

Next.js with TypeScript and Tailwind on the front end and API layer, Clerk for auth with SHA-256 hashed API keys, Neon Postgres with Drizzle ORM, Redis for caching, and Stripe for billing. The extraction layer is a Python and FastAPI service. Speech-to-text uses Whisper-class models. The MCP server is published in the official Model Context Protocol registry with a DNS-verified namespace.

ZeroScam's answer

ZeroScam is currently used by individual users and early adopters.