LaunchDeck.Me's answer

• Purpose-built for fundraising decks, not generic slides — narrative, structure, and layouts tuned for investor storytelling.
• Speed: go from a short brief to a full deck in minutes, not a multi-hour manual build.
• Large template library (50+) plus layout archetypes the AI fills per slide.
• Bring your own AI: works with multiple providers (e.g. OpenAI, Gemini, Ollama) and your own API keys when configured that way.
• Editable outputs: live editing, speaker notes, and export to PDF and PPTX (real decks, not only flat images).
• Optional web research to ground content in fresher context when you enable it.
• Open-source core (per your public positioning) for teams that want transparency and control over how presentations are generated.

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.

LaunchDeck.Me's answer

• Faster path to a complete pitch narrative — less time writing and restructuring slides from scratch in a general-purpose editor.
• Investor-oriented templates and slide patterns vs. starting from blank or generic business decks.
• Flexibility on AI — use the model stack you prefer (cloud or self-hosted) instead of being locked to one vendor’s assistant.
• Practical deliverables — PPTX for last-minute edits and PDF for sharing; no design tool learning curve required.
• Generous way to try it — free tier with 3 decks per month and no card up front (as marketed on-site).

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.

LaunchDeck.Me's answer

Founders and small teams raising money or explaining traction — especially pre-seed and seed — plus operators who need a credible deck quickly (sales, partnerships, accelerators, demo days). Secondary audience: anyone who wants professional presentations without spending days on layout and copy.

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.

LaunchDeck.Me's answer

LaunchDeck exists because building a convincing pitch deck is slow, repetitive work — merging narrative, data, and design — while fundraising timelines are not. The product was built to compress that workflow: describe the company once, let AI propose structure and copy, apply proven presentation patterns, and ship something you can edit and export the same day.

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.

LaunchDeck.Me's answer

Next.js, React, TypeScript, Tailwind CSS, Radix UI primitives. Backend: FastAPI (Python) API server (monorepo under servers/). Other notable libs/tools: Redux Toolkit, TipTap, Zod, Puppeteer/related tooling where exports or rendering need headless browser support — plus integrations with LLM providers (OpenAI, Google Gemini, Ollama, etc.) depending on deployment configuration.

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.

LaunchDeck.Me's answer

• Customer names are not publicly disclosed; the product primarily serves individual founders and small teams on a self-serve basis.