Ten portfolio companies across media, software, education, environmental services, financial services and the built environment. This portal is the working blueprint: 200 prioritised AI use cases, each scoped as a mini-spec ready to staff, fund and ship. From Ticketek's demand curves to Are Media's archive, Architectus's design practice and Findex's advisor book. See the four live agent demos →
Live entertainment and ticketing · Ticketek · TEG Dainty · TEG Live · TEG Sport · TEG Experiences
A data-rich, two-sided network — fans on one side, promoters, teams and venues on the other — with Ticketek sitting on 20+ years of transactional signal. AI's leverage points cluster around three things: lifting yield on every event through dynamic pricing and demand forecasting, growing lifetime value of ticket buyers via personalised event and merch recommendations, and compressing the cost of running tours, venue ops and customer service as volume scales.
Fixed-tier pricing leaves yield on the table for in-demand shows and slow-moving inventory in the long tail; prices should flex by seat quality, demand curve, resale signal and buyer type.
Promoters set tour routing, venue size and marketing spend on gut and comparables; forecasting demand by market before on-sale sharpens every one of those decisions.
Most Ticketek buyers see one event in a lifecycle; a personalised 'next event' engine across sport, music, arts and family lifts cross-sell and repeat rate.
High-demand on-sales are overrun by bots and resale harvesters; the current defences are rule-based and leak into Ticketek Marketplace.
Refund, access and exchange queries spike around on-sales and event days; a triaging agent across voice, email and chat deflects the long tail.
Marketplace resale is a brand risk when prices run; AI signals to cap, warn or hold listings protect fans and promoter relationships.
Gate congestion at major events (stadium shows, grand finals) damages NPS; CV on CCTV plus queue analytics reroutes staff in real time.
TEG Dainty tour feasibility is a spreadsheet-heavy pre-deal exercise; an agent that models P&L under venue, price and marketing scenarios cuts cycle time.
Brands briefing TEG for rights and activations are matched manually against events; an AI matcher across the event calendar lifts sell-through on inventory.
Tour merch overstock and stock-outs are routine; event-level forecasting on size, style and SKU cuts both.
The 'know before you go' and post-event sequences are hand-crafted per show; a generation agent on the event template library runs at Ticketek's full event volume.
Promoters wait days for post-on-sale and post-event reporting; a natural-language analytics layer over the data warehouse turns it into self-serve.
Ticketek doesn't run a group loyalty programme; an AI-designed one informed by cross-brand purchase history is a defensible moat before competitors build theirs.
Season packs, mini-plans and festival multi-day tickets are static; an agent that composes packs per buyer and per event lifts average basket.
Incidents at large events (medical, security, weather) are managed on radio and whiteboard; an incident-log agent gives ops a live picture.
Deal memos and long-form rights contracts need abstracting for commercial, finance and tour ops; a contract-reading agent compresses cycle time by weeks.
Ticketek event detail pages are populated unevenly by promoters; an AI writer standardises description, SEO metadata and FAQ at scale.
Millions of historic buyers haven't transacted in 24+ months; a propensity-scored win-back engine re-engages the dormant book.
International tours need localised event pages; machine translation plus human review runs them in days instead of weeks.
Face-value tickets flipping on secondary markets damage trust; a detection and takedown workflow protects the primary channel.
