nimatica
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2025

transcription.solutions

SaaS for audio and video transcription

transcription.solutions turns audio and video into text: a transcript with speaker labels, an AI summary and exports in seven formats. We built the product itself: the file-processing backend, the dashboard and the billing. Then we ran the search marketing for it.

The task

The client needed a working service, not a page about one. A user uploads a file or pastes a link, the job goes through a queue, and a finished transcript with a summary lands in their account. Behind that sit a processing backend, a dashboard and paid plans under one login.

The second half of the task was where the users come from. The product sells to an international audience, so the site was built for search from the start: feature pages, tool pages, use-case pages and a blog, planned around what people actually type.

What we built

Software development for a transcription service

The front door takes three inputs: upload a file, paste a link, or record in the browser. Accepted formats and limits are written next to the box, so nobody uploads a file the service will refuse.

Behind the box is the pipeline: the file joins a queue, gets transcribed, gets split by speaker and comes back with a summary. Job status updates live, so a user watches the progress instead of reloading the page.

First screen of transcription.solutions: the rotating headline, a waveform and the upload box with three tabs: file, link and record

The dashboard is shown on the page itself

Instead of describing the account, the home page puts the real interface on it. Tabs switch, action items toggle, and the summary block shows key points, topics and word counts. It is the same layout a user gets after a job finishes.

It answers the question people ask before signing up: what do I actually get back. Under it, one file is shown with the eight things derived from it, from the timestamped transcript to the export formats.

The working dashboard on the home page: a summary with key points, action items and topic tags over a blue panel

Plans, limits and billing

Three plans, monthly or annual, with the limits written on the card: minutes per month, maximum file length, which features unlock. The free plan needs no card, and that is where most people start.

Billing is part of the product rather than a page about it. The plan an account is on decides the file length, the monthly minutes and the queue priority.

The pricing block with a monthly and annual switch and three plan cards

Search marketing for a SaaS product

The site is built to be found. Feature pages, free tool pages, use-case pages and a blog each answer a separate query, and every one of them leads back to the same product.

The home page names its audiences in their own words: podcasters, researchers, small teams. A visitor from search lands on a page about their own job.

Three audience cards on the home page: podcasters, researchers and small teams, each with its own scenario

Under the hood

Under the interface sit the recognition engines, the payment rail and the markup that gets the product found. Here is what was built inside and what anyone can check from outside.

Search and AI answers

  • Languages and hreflang tags

    The public site is set up for 100 locales and the dashboard for 111, right-to-left languages included.

  • Structured data on the pages

    The pages carry JSON-LD markup of the Organization, SoftwareApplication and FAQPage types.

  • A sitemap of 3,939 addresses

    The sitemap is generated by the site itself and lists 3,939 addresses; robots.txt points to it. The sitemap

  • A file written for language models

    The site publishes llms.txt and a full version of it: a description of the product written for language models rather than for people. llms.txt

Recognition

  • Recognition with a spare engine

    Speech goes to AssemblyAI Universal-2, which separates the speakers itself.

  • Summaries through a model router

    The summary and the action items are written by a language model reached through OpenRouter, with a second model set as a fallback.

  • A bot on Zoom, Meet and Teams

    The bot joins a call on Zoom, Google Meet or Microsoft Teams through Recall.ai.

Export

  • Seven formats out of one job

    A finished transcript leaves as TXT, SRT, VTT, DOCX, Markdown, JSON or PDF.

Money

  • Subscription and minute packs

    Payments run on Stripe.

Law

  • Privacy, terms and refunds

    Three legal pages are published and linked from the footer: the privacy policy, the terms and the refund rules. Privacy policy

On a phone

transcription.solutions on a phone: the headline, the upload box and the figures about languages and accuracy in one column
transcription.solutions on a phone: the headline, the upload box and the figures about languages and accuracy in one column

What came out of it

  • Live on the international market, traffic comes from organic search
  • Six ways into the service, including a public REST API
  • The dashboard is open on the home page, before signing up

The product and its marketing run as one system. Search brings people in, the free plan lets them try the service on their own file, and the paid plans carry the ones who come back. Development and search work are done by the same hands, so a new page does not wait for a hand-off.

Need something like this?

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Questions about this project

  • A backend that accepts files and processes them in a queue, a dashboard where the results live, plans with limits and billing, and the public site around all of it. Each part is separate work, built to fit the others.

  • Yes. Plans, monthly and annual billing and the limits that come with each plan are part of the product. What a user is allowed to do is decided by the plan their account is on, not by a separate admin step.

  • Similar projects start from the Software development tariff; the prices page shows the current figure. What moves it is how much of the product is new and how heavy the file processing behind it has to be.

  • Through the structure of the site. Feature pages, tool pages and use-case pages each answer one query and link back to the same service, so search work runs on pages that already belong to the product instead of on separate landing pages.

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