Who should use the Content Aggregation 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 content aggregation with clear steps, mapped tools, and delivery-focused outcomes.
Deliverable outcome
Data-driven refinements to your aggregation workflow, leading to higher relevance and engagement over time.
30-90 minutes
Includes setup plus initial result generation
Free to start
You can swap tools by pricing and policy requirements
Data-driven refinements to your aggregation workflow, leading to higher relevance and engagement over time.
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 Zapier to a documented source list with clear criteria for what content to pull and how often. Then, you pass the output to n8n to a unified raw content table with deduplicated entries, ready for processing. Then, you pass the output to Together AI to a cleaned, enriched dataset with consistent formatting and optional ai-generated summaries. Then, you pass the output to CellFormula AI to every content item tagged with at least one category and relevant keywords, ready for filtering. Then, you pass the output to Arcwise AI to a shortlist of high-value, curated content items ready for formatting and distribution. Then, you pass the output to Buffer to curated content published or scheduled across all target channels with consistent branding. Finally, Onvo AI is used to data-driven refinements to your aggregation workflow, leading to higher relevance and engagement over time.
Define Content Sources & Criteria
A documented source list with clear criteria for what content to pull and how often.
Fetch & Ingest Raw Content
A unified raw content table with deduplicated entries, ready for processing.
Clean & Enrich Content
A cleaned, enriched dataset with consistent formatting and optional AI-generated summaries.
Categorize & Tag Items
Every content item tagged with at least one category and relevant keywords, ready for filtering.
Curate & Prioritize Final Selection
A shortlist of high-value, curated content items ready for formatting and distribution.
Format & Distribute to Channels
Curated content published or scheduled across all target channels with consistent branding.
Monitor Performance & Iterate (Optional)
Data-driven refinements to your aggregation workflow, leading to higher relevance and engagement over time.
Identify and list the RSS feeds, social media accounts, news sites, or APIs you want to aggregate from. Set inclusion/exclusion keywords, content types (articles, videos, images), and update frequency. This step ensures you pull only relevant material and avoid noise.
Why Zapier: Zapier can connect to RSS feeds and APIs to define content sources and trigger workflows based on new content, fitting the need for an RSS reader or API management tool.
Use automated scripts or no-code connectors to pull the latest items from each source. Store the raw data (titles, bodies, media URLs, timestamps) in a central database or spreadsheet. This step transforms scattered sources into a single, queryable dataset.
Why n8n: n8n is an AI agent orchestration tool that can build data ingestion pipelines, aligning with the need for a data ingestion pipeline like n8n or Make.
Strip HTML tags, remove boilerplate text, and extract key metadata (author, publish date, reading time). Optionally enrich with AI-generated summaries, sentiment tags, or entity extraction. This step improves content quality and makes it easier to categorize later.
Why Together AI: Together AI provides access to open-source LLMs for inference, which can be used to enrich content via an LLM API, complementing text processing libraries.
Assign each item to predefined categories (e.g., 'Industry News', 'Product Updates', 'Thought Leadership') and add tags for topics, brands, or urgency. Use keyword rules or an AI classifier to automate this. Proper categorization enables targeted distribution.
Why CellFormula AI: CellFormula AI includes regex construction, which is a key part of building a tagging engine for categorizing and tagging items.
Review the tagged items and manually or algorithmically select the top pieces for distribution. Apply a priority score based on recency, source authority, or engagement potential. This step ensures only the most valuable content reaches your audience.
Why Arcwise AI: Arcwise AI provides natural language formula generation and automated data cleaning, which can help in sorting and filtering content in a spreadsheet-like environment.
Transform each selected item into the required format for each output channel (e.g., email newsletter, social media post, blog roundup). Include title, summary, link, and optional media. Automate the publishing via APIs or scheduling tools.
Why Buffer: Buffer is a multi-platform scheduling tool that can distribute content to social media channels, fitting the distribution platform requirement.
Track open rates, click-through rates, or engagement metrics for each distributed item. Compare performance against your criteria to refine source selection, tagging rules, and prioritization. This step closes the loop for continuous improvement.
Why Onvo AI: Onvo AI can generate dashboards from natural language prompts and automate report generation, serving as an analytics dashboard for monitoring performance.
§ 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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