Time to first output
30-90 minutes
Includes setup plus initial result generation
Execution Map
Step-by-step pipeline
Step 1 of 7Open task page
Preparation: Image Generation
Prepare inputs and settings through Image Generation before running retrieval-augmented generation (rag).
Why it matters
Image Generation sets up the foundation for retrieval-augmented generation (rag); clean inputs here reduce downstream rework.
The Result
Inputs, context, and settings are ready so the workflow can move into execution without blockers.
⭐Top PickTop mapped tool
BlueWillow →Selected from the highest-fit tool mappings and active usage signals for this step.
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Step 2 of 7Open task page
Input Setup: AI Logo Generation
Use AI Logo Generation to build supporting assets that improve retrieval-augmented generation (rag) quality.
Why it matters
AI Logo Generation strengthens retrieval-augmented generation (rag) by feeding better supporting material into the pipeline.
The Result
Supporting assets from ai logo generation are prepared and connected to the main workflow.
⭐Top PickTop mapped tool
Looka →Selected from the highest-fit tool mappings and active usage signals for this step.
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Compare top toolsStep 3 of 7Open task page
Input Setup: AI Video Generation
Use AI Video Generation to build supporting assets that improve retrieval-augmented generation (rag) quality.
Why it matters
AI Video Generation strengthens retrieval-augmented generation (rag) by feeding better supporting material into the pipeline.
The Result
Supporting assets from ai video generation are prepared and connected to the main workflow.
⭐Top PickTop mapped tool
VEED →Selected from the highest-fit tool mappings and active usage signals for this step.
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Compare top toolsStep 4 of 7Open task page
Core Execution: Retrieval-Augmented Generation (RAG)
Execute retrieval-augmented generation (rag) with Retrieval-Augmented Generation (RAG) to produce the primary final deliverable.
Why it matters
This is the core step where retrieval-augmented generation (rag) actually happens, so it determines baseline quality for everything after it.
The Result
A first-pass final deliverable is generated and ready for refinement in the next steps.
⭐Top PickTop mapped tool
AI21 Studio →Best mapped choice for the core step based on task relevance and active usage signals.
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Quality and Optimization: Video Generation
Refine and validate retrieval-augmented generation (rag) output using Video Generation before final delivery.
Why it matters
Video Generation adds quality control so issues are caught before the workflow is finalized.
The Result
The final deliverable is improved, validated, and prepared for final delivery.
⭐Top PickTop mapped tool
Hedra →Selected from the highest-fit tool mappings and active usage signals for this step.
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Quality and Optimization: AI Image Generation
Refine and validate retrieval-augmented generation (rag) output using AI Image Generation before final delivery.
Why it matters
AI Image Generation adds quality control so issues are caught before the workflow is finalized.
The Result
The final deliverable is improved, validated, and prepared for final delivery.
⭐Top PickTop mapped tool
Adflow →Selected from the highest-fit tool mappings and active usage signals for this step.
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Delivery: Knowledge Retrieval
Package and ship the output through Knowledge Retrieval so retrieval-augmented generation (rag) reaches end users.
Why it matters
Knowledge Retrieval is what turns intermediate output into a usable, publishable result for real users.
The Result
A finalized final deliverable is ready for publishing, handoff, or integration.
⭐Top PickTop mapped tool
Personal.ai →Selected from the highest-fit tool mappings and active usage signals for this step.
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