Who should use the OCR workflow?
Teams or solo builders working on work tasks who want a repeatable process instead of one-off tool experiments.
AI Workflow · Work
Practical execution plan for ocr with clear steps, mapped tools, and delivery-focused outcomes.
Deliverable outcome
A finalized document output is ready for publishing, handoff, or integration.
30-90 minutes
Includes setup plus initial result generation
Free to start
You can swap tools by pricing and policy requirements
A finalized document output is ready for publishing, handoff, or integration.
Use each step output as the input for the next stage
Step map
Instead of relying on a single generic AI model, this pipeline connects specialized tools to maximize quality. First, you'll use Places365 to inputs, context, and settings are ready so the workflow can move into execution without blockers. Then, you pass the output to Syte to supporting assets from visual search are prepared and connected to the main workflow. Then, you pass the output to ChatGPT to supporting assets from conversational ai are prepared and connected to the main workflow. Then, you pass the output to Candis to a first-pass document output is generated and ready for refinement in the next steps. Then, you pass the output to Tenstorrent to the document output is improved, validated, and prepared for final delivery. Then, you pass the output to Generative Scene Networks (GSN) to the document output is improved, validated, and prepared for final delivery. Finally, Reface is used to a finalized document output is ready for publishing, handoff, or integration.
Semantic Segmentation
Inputs, context, and settings are ready so the workflow can move into execution without blockers.
Visual Search
Supporting assets from visual search are prepared and connected to the main workflow.
Conversational AI
Supporting assets from conversational ai are prepared and connected to the main workflow.
OCR
A first-pass document output is generated and ready for refinement in the next steps.
AI Model Inference
The document output is improved, validated, and prepared for final delivery.
Novel View Synthesis
The document output is improved, validated, and prepared for final delivery.
Face Swapping
A finalized document output is ready for publishing, handoff, or integration.
Prepare inputs and settings through Semantic Segmentation before running ocr.
Semantic Segmentation sets up the foundation for ocr; clean inputs here reduce downstream rework.
Inputs, context, and settings are ready so the workflow can move into execution without blockers.
Use Visual Search to build supporting assets that improve ocr quality.
Visual Search strengthens ocr by feeding better supporting material into the pipeline.
Supporting assets from visual search are prepared and connected to the main workflow.
Use Conversational AI to build supporting assets that improve ocr quality.
Conversational AI strengthens ocr by feeding better supporting material into the pipeline.
Supporting assets from conversational ai are prepared and connected to the main workflow.
Execute ocr with OCR to produce the primary document output.
This is the core step where ocr actually happens, so it determines baseline quality for everything after it.
A first-pass document output is generated and ready for refinement in the next steps.
Refine and validate ocr output using AI Model Inference before final delivery.
AI Model Inference adds quality control so issues are caught before the workflow is finalized.
The document output is improved, validated, and prepared for final delivery.
Refine and validate ocr output using Novel View Synthesis before final delivery.
Novel View Synthesis adds quality control so issues are caught before the workflow is finalized.
The document output is improved, validated, and prepared for final delivery.
Package and ship the output through Face Swapping so ocr reaches end users.
Face Swapping is what turns intermediate output into a usable, publishable result for real users.
A finalized document output is ready for publishing, handoff, or integration.
§ Before you start
Teams or solo builders working on work tasks who want a repeatable process instead of one-off tool experiments.
No. Start with the top pick for each step, then replace tools only if they do not fit your pricing, compliance, or output needs.
Open the mapped task page and compare top options side by side. Prioritize output quality, integration fit, and predictable cost before scaling.
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