Embeddings
Generate vectors for large corpora.
For Developers
Batch AI workloads at lower cost.
Submit jobs through API or dashboard and receive verified results automatically.
Supported workloads
Built for batch work, not live serving.
Transcription
Convert audio archives into text.
OCR
Extract text from documents and scanned PDFs.
Dataset preprocessing
Prepare inputs for downstream workflows.
Image inference
Run image jobs that can wait for verified completion.
Best use cases
Fit the workloads that do not need premium always-on cloud pricing.
Index millions of documents overnight
Use distributed compute when throughput matters more than latency.
Transcribe audio archives
Process historical libraries as a batch queue.
Prepare training datasets
Run the boring parts of the pipeline on cheaper compute.
Process scanned PDFs
Convert document backlogs into structured text.
Run large embedding pipelines
Scale out work without paying hyperscaler prices for idle capacity.
Sample API flow
Upload dataset. Submit job. Track progress. Download results.
Upload dataset
Send the input the job needs.
Submit job
Create the workload from the dashboard or API.
Track progress
Watch verification and completion state as the job runs.
Download results
Fetch output when the verified work is done.
POST /customers/jobs
GET /customers/jobs/{job_id}
GET /customers/me
Input: dataset URI or uploaded artifacts
Output: verified batch resultsIntegrations
Designed to fit the tools teams already use.
LangChain
Useful when Common Compute is one backend in a larger pipeline.
LlamaIndex
Fits indexing and retrieval workflows.
Airflow
Use scheduled batch orchestration.
Ray
Coordinate distributed tasks across the network.
Prefect
Keep the job flow explicit and observable.
Get started
Run a benchmark.
Submit a workload and see verified results before committing.