An AI curated news API should feel like an extension of a newsroom: careful with sourcing, honest about limits, and fast enough to matter. With FeedsAI.com on the masthead, that standard is non-negotiable. This guide walks through the decisions required to build an AI curated news API that editors, analysts, and partners will trust.
Clarify the editorial north star
Before any code, define what the API will and will not publish.
- Coverage scope. Choose beats: markets, security, policy, product, or sector-specific news. Avoid claiming “everything” when you cannot staff it.
- Source criteria. Create a whitelist with licensing, recency, and fact-checking track records. Require at least two independent sources for sensitive topics.
- Bias checks. Monitor source diversity to avoid skew. Include regional and language diversity where relevant.
- Corrections policy. Document how corrections flow into the feed and how long they stay visible.
Curate with a transparent pipeline
Curation should be explainable. Treat each step as part of the story.
- Ingest with metadata. Capture author, publication, timestamp, and URL. Store the raw HTML and a cleaned version for reference.
- Relevance filters. Use keyword, entity, and topic models to decide inclusion. Store relevance scores and make them queryable.
- Duplicate controls. Deduplicate by URL, canonical link tags, and content hashes. Keep a pointer to the earliest instance.
- Sensitivity flags. Mark items containing personally identifiable information or unverified claims, and handle them separately.
Summaries that keep context intact
Summaries are where many AI curated news API efforts stumble. Guard against drift.
- Prompt discipline. Use structured prompts that ask for headline, 3-5 bullets, and explicit citations. Remind the model to quote rather than invent numbers.
- Source quoting. Include the outlet name and publish time in the output so users see provenance alongside the summary.
- Length tiers. Offer micro-summaries for notifications, briefs for executives, and full paragraph summaries for analysts.
- Human-in-the-loop. Allow editors to pin or amend summaries for sensitive topics, then treat the edited version as canonical.
Enrichment that helps search and ranking
Enrichment should make the feed easier to search and rank without obscuring origin.
- Entity extraction. Use deterministic extractors for companies, people, and products. Keep a confidence score on every entity.
- Topic tagging. Map articles to a controlled taxonomy. Avoid freeform tags that make filters brittle.
- Geo and language. Detect geography and language at ingest. Offer translation where licensing allows, and include the detected values in metadata.
- Embeddings on ingest. Generate embeddings for semantic search and clustering. Store the model version so you can regenerate when it changes.
Delivery models that fit real users
Not every consumer wants the same interface. Provide sensible choices.
- REST for bulk and history. Offer paginated history with filters for source, topic, and confidence bands.
- Webhooks for urgency. Deliver to webhooks when high-priority topics publish. Include retries and signed payloads.
- Briefs for executives. Package the same content into briefs with skimmable bullets and calls to action.
- Widgets and cards. Ship embeddable cards for product teams that want to surface curated news inside their apps.
Reliability and governance guardrails
A curated news API is judged on what it excludes as much as what it includes.
- Quality thresholds. Enforce minimum source quality and ban outlets that repeatedly fail checks.
- Uptime discipline. Publish your latency and uptime targets. Monitor p95 end-to-end time from source publication to API availability.
- Takedowns. Create a documented path for removing content when requested by publishers or regulators. Keep audit logs.
- Licensing clarity. Store license details per source and expose them so customers know where redistribution is allowed.
Productizing FeedsAI.com as the home for curation
Use the domain to reinforce the idea that the feed is careful, not generic.
- Messaging. Lead with “AI curated news API with provenance” not “AI does the news.” Make provenance and latency the heroes.
- Onboarding. Give new developers a sandbox token and example sources. Show them how to test deduplication and summaries.
- Feedback loops. Accept user flags on questionable items and loop them back into curation metrics.
- Roadmap honesty. Publish when new beats are coming and which sources are in pilot.
The AI curated news API outlined here keeps humans in the loop, codifies standards, and uses FeedsAI.com as a promise of rigor. Ship it with transparency and the brand will stand for more than a clever name.