AI-powered system that scrapes event data, filters relevant events, consolidates information, and publishes color-coded events to Google Calendar. Features intelligent event categorization and automated scheduling.
Event managers, tourism bodies, industry associations and community organisations often maintain calendars pulled from many places: venue websites, ticketing platforms, member submissions and council listings. Copying details by hand is slow, the same event appears several times under slightly different names, and irrelevant listings clutter the calendar. By the time a shared calendar is updated, some events have already changed.
Event calendar automation collects listings from permitted sources, uses AI to match duplicates, filter out irrelevant entries and categorise the rest, then publishes them to shared Google Calendars with consistent colour coding. Staff review borderline items instead of processing every listing, and subscribers see an organised, colour-coded calendar that updates regularly without anyone copying details across by hand.
Scheduled jobs collect listings from event feeds, ticketing APIs, iCal links and websites whose terms permit collection, storing raw records with their source.
An LLM normalises each record into a standard structure covering title, date, time, venue, organiser, price type and description.
Duplicate detection compares titles, dates and venues to merge listings of the same event, keeping the most complete details and all source links.
The AI classifies events by type and relevance against the organisation's criteria; low-confidence items go to a review queue.
Approved events are published through the Google Calendar API to the right shared calendar with colour codes, and updates or cancellations are synced.
An event management company uses AI to automatically scrape events from multiple sources, remove duplicate or irrelevant entries, categorize events by type and importance, and publish them to shared Google Calendars with appropriate color coding and notifications.
Web scraping tools, AI event filtering, Google Calendar API, Event categorization algorithms, Data consolidation systems
Check each source's terms before scraping; many ticketing sites prohibit it and offer APIs or partner feeds instead. Event descriptions and images are often protected under the Copyright Act 1968, so publish short factual summaries with a link back to the original rather than copying full text or images. If listings include organisers' personal contact details, handle them under the Privacy Act 1988 or omit them. Descriptions of prices or availability must stay accurate to avoid misleading the public under the Australian Consumer Law, so link to the official listing for ticket details.
This solution requires careful evaluation of cost-benefit ratio. Consider implementation only after thorough analysis and risk assessment.
Technically many sites can be scraped, but terms of service often prohibit it and some content is copyright protected. The better approach uses official feeds, ticketing APIs, iCal links and partnerships, reserving scraping for sites that allow it. Publishing short summaries with links keeps you on safer ground.
It reads each normalised event and assigns categories and a relevance rating using your defined criteria and examples. Clear definitions with examples of what belongs in each category improve accuracy. Items the model is unsure about go to a reviewer, and corrections can be added as further examples.
Two to four weeks is typical. Time goes into confirming sources, building collectors, defining categories, tuning duplicate detection and connecting Google Calendar. Starting with a handful of reliable sources and adding more once the pipeline is stable reduces maintenance headaches.
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