Why use an AI content generation API?
You already know AI can write content quickly. What many teams aren't aware of, however, is that feeding a raw large language model directly into a production content pipeline is often where the cracks begin to show. Unfiltered LLM output can be overly formulaic, gets flagged by Originality.ai and GPTZero, neglects search engine optimization structure, and requires an additional pass just to include images, meta data, and internal links.
That's a whole lot of glue code for a task that really ought to be a single HTTP call. That's where the SpeedContent AI content generation API comes in. You give us a keyword, we give you a fully humanized, SEO-optimized article with headings, a meta description, a featured image, and authoritative outbound links all set and ready to publish.
One endpoint, one job ID, one polling loop.
What you get in a single API call
All articles the API generates go through six internal stages you won't need to manage. First, we generate an outline that aligns with your keyword and content type. Then Claude writes a 500–3000 word long-form article with the appropriate heading structure.
That draft is sent through our humanization engine, which ensures it passes GPTZero, Originality.ai, and Copyleaks — most outputs produce an AI score below 20. The article is then optimized with an SEO pass that adjusts keyword density, creates a meta description, and inserts internal links. A featured image is created and hosted on our CDN. Finally, outbound authority links to relevant sources are added.
You receive one JSON response with the article as markdown, the image URL, and the final AI score. That's the whole integration.
Fire-and-poll pattern
Article generation takes 60–120 seconds, so the API is asynchronous. You submit a job, get the job ID back immediately, then poll every 10 seconds until the status changes to completed.
Submit a job
curl -X POST https://generatecontentwithaiservice-g5zrtckfda-ue.a.run.app/api/v1/generate \
-H "Authorization: Bearer sc_your_api_key" \
-H "Content-Type: application/json" \
-d '{
"keyword": "best running shoes 2026",
"target_words": 1200,
"tone": "Friendly",
"content_type": "Listicle",
"generate_image": true
}'
You get back a job_id and an estimated_seconds value immediately — no waiting.
Poll for the result
curl https://generatecontentwithaiservice-g5zrtckfda-ue.a.run.app/api/v1/jobs/JOB_ID \
-H "Authorization: Bearer sc_your_api_key"
When status flips to completed, the article, image_url, and ai_score fields are all populated.
Parameters worth knowing
The primary keyword is mandatory — it is the phrase you want to rank for on Google. You can specify up to two secondary keywords that get naturally integrated into the text. Target word count varies between 500 and 3000; larger targets take proportionally more time but tend to rank better for competitive queries.
Style, tone, and content type let you tailor the article to your voice and format — informational, listicle, how-to, product review, or comparison. For tight control over the shape of the output, pass an explicit article_structure array of H2/H3 headings and the AI will follow it. Image generation defaults to on, and image_variant (fast, standard, or ultra) lets you trade speed for quality.
Common patterns developers use
Batch generation for programmatic SEO is one of the most typical use cases. If you're building 200 pages for cities within a local service, fire jobs concurrently up to your rate limit of five per key, then poll each in turn. One Node script can produce 200 unique articles in under an hour.
Newsroom-style content pipelines are another popular shape. Wire the API directly to a Google Sheet of trending queries via Make.com or n8n. Every new row kicks off a job, polls the article to completion, and publishes the result to WordPress or Ghost via their own APIs. The pipeline requires no LLM prompt engineering on your part.
White-label integration inside your own SaaS is a third common pattern. If you sell a marketing tool, add article generation as a feature of your product without building a whole LLM stack. Your users click a button in your UI, you call our API from your servers, and stream the finished article back into their editor.
Rate limits and pricing
All API keys are limited to five concurrent jobs. If you exceed that, a 429 response is returned. Credit cost per job depends on word count and image variant. Failed jobs are refunded automatically, so you only ever pay for successful generations.
Why not just call an LLM yourself?
If you were to assemble the same stack from scratch, you'd be handling prompt engineering, outline creation, humanization (a multi-model pipeline in itself), Originality.ai testing, image generation, meta description writing, and maintaining all of it as the underlying models drift. The SpeedContent API is that entire stack built for you, priced per article, with a single Bearer token.
Start building
Get your API key from the API Keys page in the SpeedContent dashboard. Credits are provided for free signups so you can run the API end to end on real keywords before upgrading.