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Bulk Transcript lets you paste up to 50 Instagram Reel, YouTube Shorts, or TikTok URLs at once and get every transcript back in a single batch. No file downloads, no one-at-a-time processing. What used to take content creators 4 hours now takes 30 minutes โ paste your links, switch to other work, come back to a finished batch.
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I'm a content creator making around 30 videos a week โ UGC, opinion pieces, and tech content. Getting inspiration from other creators meant transcribing their videos, and every tool I found only let me do one at a time. What should have been a quick research step was eating 4 hours of my day. I built Bulk Transcript to fix that for myself, and it turned a 4-hour process into 30 minutes. Once it worked for me, I made it available to everyone.
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Competitors like Otter.ai, Rev, and Descript are built for long-form audio and require file uploads or app installs. Bulk Transcript is built specifically for short-form social video โ paste URLs directly, process in bulk across platforms, and download as TXT or SRT. It's pay-as-you-go with credits that never expire, so you're not locked into a monthly subscription for something you use occasionally.
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Content creators repurposing Reels and Shorts into written content, social media managers and agencies doing competitor script research at scale, and marketers analyzing hooks and CTAs across short-form video.
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Next.js, React, Tailwind CSS, TypeScript. Transcription powered by OpenAI Whisper.
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Based on our record, Apache Kafka seems to be more popular. It has been mentiond 155 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Kafka is a distributed streaming platform used to build real-time data pipelines and streaming applications. It allows producers to send messages to topics, which are then consumed by various consumers, making it ideal for event-driven architectures. - Source: dev.to / 2 months ago
Apache Kafka is the most widely used distributed event streaming platform and the standard transport layer for event-driven reconciliation architectures. - Source: dev.to / 3 months ago
For message-queue-based pipelines: RabbitMQ has native DLQ support through dead letter exchanges. Messages that exceed their retry count or their time-to-live are automatically routed to a designated DLQ exchange. Apache Kafka does not have native DLQ semantics, but the standard pattern is to write failed records to a dedicated topic (-dlq by convention) and include the failure metadata in the record headers. - Source: dev.to / 3 months ago
Upsert with timestamp tracking. Keep the upsert approach but track which time windows have been fully processed. On retry, skip windows that are marked complete and reprocess only windows that failed mid-run. The Kafka documentation covers offset management patterns that implement this for stream-based pipelines. - Source: dev.to / 3 months ago
Apache Kafka allows the payment service to publish a transaction event to a topic, without knowing who will consume it. The fraud service, the notification service, and any other interested component can subscribe to that topic independently:. - Source: dev.to / 3 months ago
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