Agentic backend-as-a-service
The agentic backend
for developers.
Long-running, multi-step agents that plan, call tools, and run to a finished result. Server-side. One API key. Any app.
Live · No signup
See it run.
Open a playground, send inputs, watch a real agent work end to end.
How it works
Prompt to production.
Three steps.
No servers. No queues. Write the agent, push it, call it.
- 01
Write a skill
A system prompt plus the tools your agent can call. The model plans, uses them, and iterates until the work is done.
- 02
Push your skillpack
Bundle it and deploy as one versioned release. Activating a new version is a rolling switch — in-flight jobs keep running on their version.
- 03
Call it as a job
One endpoint, one body shape, from any app with a workspace API key. Submit inputs, read the result.
curl -X POST https://api.puras.co/v1/jobs \
-H "Authorization: Bearer $PURAS_API_KEY" \
-d '{"skill":"deep-research","inputs":{"topic":"..."}}'One endpoint
Three ways to call it.
Pick your latency. Same job — fire-and-forget, awaited, or streamed token by token.
Async
POST /v1/jobsFire and forget — returns immediately, poll for the result when you want it.
Sync
?wait=true&timeout=30Block until the job is done, up to 60 seconds. Perfect for fast skills.
Stream
?stream=trueAn SSE stream of every tool call and model response, live as the agent works.
Generative media
Image, video, audio.
Built in.
Your agents call the best image, video, and audio models through one surface — billed per call, files land in the workspace drive, ready to hand back to your app.
The agent picks the model at runtime. No wiring per model.
from puras import media
img = media.run("openai/gpt-image-2", {"prompt": "a vintage red bicycle"})
clip = media.run("kuaishou/kling-v3-i2v",
{"image_url": img["output_url"], "prompt": "make it spin"})Observability
Metered to the cent.
Long-running agents are opaque by default. puras makes every run auditable.
Every job has a price tag
Each job returns its total cost, with a line-item breakdown of every model call — which model, how many tokens, what it cost.
See the agent think
A full event log per job, streamable live — every tool call, model response, and error as it happens.
Pay only for what runs
Pay-as-you-go, no subscriptions or minimums. Top up your workspace balance once; jobs draw it down as they run.
Dev loop
Deploy without leaving
your editor.
Push your whole skillpack as one deployment, one call. No git remote, no Docker, no CI. The MCP server lets Claude Code and Cursor push and tail jobs for you.