Video generation API: create videos programmatically

Text has had APIs forever. Images got them in 2022. Video is the last medium you still can't reliably produce with a POST request — most "video APIs" either render rigid templates or return raw AI footage with no voiceover, no structure, and no brand. A video generation API in the useful sense takes a prompt or a document and returns a finished, branded, narrated video your code can ship to a user. This guide covers what that unlocks, four things developers are building with it, and a six-step quickstart against Ozor's REST API — with real endpoints from the developer docs, not pseudocode.

What is a video generation API?

A video generation API is a programmatic interface that turns structured input — a text prompt, a document, a data payload — into a finished video file, without a human opening an editor. The request describes what the video should say; the service handles scene design, motion, voiceover, music, and rendering; the response hands your code an MP4 and a shareable URL.

The category hides three very different architectures. Template-rendering APIs (the Shotstack model) let you programmatically fill and render layouts you designed in advance — predictable, but every output is the same video with different values. Generative-clip APIs return short raw AI footage — impressive frames, but no narration, no information structure, and heavy post-production before anything is shippable. AI-agent APIs, the model Ozor uses, sit between: an agent interprets your prompt, designs animated motion-graphics scenes around your actual content, writes and records the voiceover, applies your brand kit, and renders the result. You get the flexibility of generation with the finish of production.

Ozor exposes that engine three ways, all sharing one credit balance and one auth model: a keyed REST API under /api/v1/ for code, an official n8n node for no-code workflow automation, and an MCP server for AI agents. This guide covers the REST surface — the right layer when video generation is embedded in your product or pipeline and you want request-level control.

What you can build with one

The pattern behind every good API use case is the same: you have structured data that would land better as a video, and the volume or freshness requirement makes manual production impossible. Four builds that fit:

• →In-product video features.Your users have content — reports, listings, lessons, portfolios — and you want a "Turn this into a video" button next to it. Your backend maps the user's data into a prompt, calls generate, polls the job, and surfaces the share link or embed in your own UI. Video generation becomes a feature of your product without your team building a rendering pipeline, and the free export step means you only spend credits when a user actually generates.
• →Personalized video at scale.One generate call per record: loop over your leads, customers, or students, inject each record's name, company, and context into the prompt, and produce a genuinely different video per person — not a template with a name swap, because the agent designs scenes around the specific context you pass. This is the engine behind personalized sales videos at scale, and at one credit per video the unit economics work at list size.
• →CI-triggered changelog videos.A release pipeline step collects merged PR titles and release notes, concatenates them into a prompt, and generates a 60-second "what shipped this week" video — posted to Slack or your changelog page by the same job that cut the release. Product updates people actually watch, produced by the deploy itself, with zero human minutes per release.
• →Marketplaces generating listing videos. Every new listing — property, job, product, course — triggers a generate call with the listing's attributes and photos (the API accepts image attachments by URL). Listings with video convert better, but no marketplace can staff video production per listing; an API call per insert can. Public exports return a permanent share URL, so the video lives on the listing page for its lifetime.
• →Document pipelines.The API's document endpoints analyze a PDF, DOCX, PPTX, or URL into an editable scene plan your code can adjust before rendering — the programmatic version of document to video AI. Point it at your knowledge base and every article gains a video counterpart.

Quickstart: Ozor's API in six steps

The full reference lives in the developer docs; this is the shortest path from nothing to a shareable video URL. Everything below is plain HTTPS with JSON bodies — no SDK required.

The fastest variant collapses steps 2, 5, and 6 into a single call by auto-exporting:

curl -X POST https://ozor.ai/api/v1/videos/generate \
  -H "X-API-Key: $OZOR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A 30-second onboarding video for our analytics dashboard",
    "aspect": "16:9",
    "export": true,
    "exportQuality": "1080p",
    "exportIsPublic": true
  }'
# -> { "videoId": "abc123", "jobId": "job_...", "status": "pending" }

Then one polling loop against the video resource covers both the agent run and the render:

curl https://ozor.ai/api/v1/videos/abc123 \
  -H "X-API-Key: $OZOR_API_KEY"
# poll every 2-3s; when "exportStatus" is "complete":
# -> { "shareUrl": "...", "shareCode": "a3kf92p",
#      "downloadUrl": "...", "thumbnailUrl": "..." }

Two error codes are worth handling explicitly: 402 means your credit balance is short for the operation (no partial work happens, nothing is deducted), and 401 means the key is missing or revoked. Everything else returns JSON with a detail field explaining what went wrong.

Ozor API vs the alternatives

"Video API" covers several products that are not actually interchangeable. Here is how the realistic options compare on the dimensions that decide an integration:

The decision usually reduces to output type. Avatar APIs are the right call when you specifically want a presenter on screen reading a script. Template renderers are right when your videos genuinely are the same layout with different values and you have a designer to build the templates. A DIY ffmpeg pipeline gives you total control at the cost of owning composition, TTS integration, rendering infrastructure, and every edge case forever.

Ozor's API is built for the case in between: explainer-style animated video where the content changes per request and the result needs voiceover, music, and brand styling without post-production. The conversational message endpoint is the part the other models lack — your code (or an agent, or a human in the editor) can iterate on a draft instead of regenerating from scratch. For how the underlying engine stacks up against the broader generation landscape, see the best AI video generator comparison; for current plan details, see pricing.

Frequently asked questions