infery
Use cases

Start with the job, not the tool

Five things people actually do here, in the order they tend to do them: make one piece, work out which model to trust, make the next twenty the same way, drive it from code, and put everyone on one balance. Pick the one that sounds like your week.

One piece

Script it, storyboard it, animate it, voice it — in one thread

Write the script in chat with whichever model you like. Ask for the scene and it arrives as an image that matches what the two of you just agreed. Animate the frame that works. Add the voiceover. Nothing gets exported, re-uploaded, or re-explained on the way.

  • The character you described in message two is the same character in the video
  • The thread survives a change of model, not just a change of tab
  • Every asset lands in the workspace, not in your downloads folder
A chat thread: the brief agreed in conversation, then the generated opening frame returned in the same thread, labelled with the model that made it.
Choosing

Send one prompt to five models. Keep the one that won.

Finding out what a model can do should not cost a subscription. Send the same prompt to as many as five at once, put the results beside each other, and have a model review them if you would rather not judge your own work. Then spend the rest of the month on the winner.

  • Up to five models per comparison, one prompt, one balance
  • An optional reviewer model scores the results for you
  • Costs credits, not another card on file
One prompt answered by three models in one panel — each answer labelled with its model, the credits it cost and how long it took — with a verdict box below arguing for one of them.
Repeat

The chain you just did by hand becomes one run

The steps you took for the first piece are a graph. Save it, and the next twenty pieces are that same graph with different inputs — including the parts that were never a model call: the crop, the transcode, the script that renames things, the search you did first.

  • Seven kinds of step and 31 named transforms — code, HTTP, web search, document parsing, video and audio work, fan-out over a list
  • Per-step artifacts, so when step five fails you can look at what step four made
  • Hand the run to someone who does not write code
A finished run mixing model steps with steps that are not models: gpt-5 writes the report and gpt-image-2 draws its cover, then document.convert_format renders a PDF and archive.pack bundles the lot — the output card holds the document, the cover and the archive.
From your code

You don't write the orchestration

One POST carries the whole graph: model calls, media generation, transforms, code, HTTP, web search, fan-out over a list. The alternative is your own queue, your own retries, your own intermediate storage and transcode — weeks of it, and then maintenance forever.

  • The canvas and the API are the same thing: read a graph as JSON, or paste a curl command to fill in an HTTP step
  • When a multimodal run fails at step five, the intermediates are images and video — you cannot read those in a log
  • Swap the base URL and keep your SDK; the same key now also reaches image, video, audio, music and 3D
http
POST /v1/pipelines
{
  "name": "Scene → clip → cut with the voiceover",
  "definition": {
    "inputs": [
      { "name": "brief", "type": "text",  "label": "Scene brief" },
      { "name": "voice", "type": "audio", "label": "Voiceover" }
    ],
    "steps": [
      { "id": "scene", "type": "media", "model": "nano-banana-2",
        "input": { "prompt": "${input.brief}" } },

      { "id": "clip", "type": "media", "model": "veo-3.1-fast",
        "input": { "prompt": "${input.brief}",
                   "image":  "${steps.scene.output.url}" } },

      { "id": "final", "type": "video.add_audio",
        "input":  { "video_url": "${steps.clip.output.url}",
                    "audio_url": "${input.voice}" },
        "params": { "mode": "replace" } }
    ],
    "output": { "video": "${steps.final.output.url}" }
  }
}
Together

One balance, one workspace, five roles

A household, a two-person studio or a ten-person agency run the same mechanic: one prepaid balance instead of seats bought ad hoc, and roles so the person who pays does not have to be the person who reads the work.

  • Five roles — owner, admin, developer, billing, viewer. A billing-only member never sees Studio data
  • Shared chats, shared runs, shared templates
  • Caps per API key: requests per minute, allowed models, and a credit budget per hour, day, week or month
A workspace members list showing five roles — admin, two developers, billing and viewer — beside the owner, with one shared credit balance in the corner.

Pick a job and try it

Free trial credits, no card. Enough to run a chain end to end and see for yourself whether the thread holds when the modality changes.