How Enterprise AI Transforms Business Data into Actionable Insights | Ep 279 | DevReady Podcast

·31 min·1 clip

Kira has twice achieved a zero-day sales close for a foundation customer.

1. DevReady Podcast episode 279 focuses on how Kira turns enterprise AI and business data into actionable insights. 2. Dina Yule is the co-founder of Knowledge Orchestrator and Kira, and Anthony hosts the DevReady Podcast while introducing her as a first-time guest to him. 3. The episode asks what enterprise AI is for when a business already has data everywhere and needs a faster “so what.” 4. Dina says her background is in sales, customer service, customer experience, and building support teams, while Dr Errol Brandt provides the technical expertise behind Kira. 5. She says they worked together at Amcor in Melbourne for about 15 years and joined a turnaround project after part of the packaging business was sold to Aurora. 6. Dina says that business had been losing about a million dollars a week before the turnaround effort. 7. She explains that Kira started as Knowledge Orchestrator, aimed at centralising business knowledge and analytics with accessibility for staff. 8. Dina says the company shifted focus from knowledge management to enterprise AI because customers wanted the analytics and AI component more than the knowledge repository. 9. She says Kira pulls together disparate source data and delivers it in plain language so people do not have to work through spreadsheets for days. 10. Dina says a sales report in Kira is personalised for each salesperson and can surface top actionable insights in real time. 11. She says one foundation customer has twice achieved a zero-day sales close, with month-start analytics ready by 9am on day one. 12. Dina says that customer has a couple of thousand customers and 50,000 products, which shows the scale Kira is handling. 13. She says the next steps are weekly analytics and then daily analytics, so trends appear earlier. 14. Dina says the product is being expanded beyond sales into working capital, inventory, procurement, and delivery performance. 15. She says Kira can layer over disparate systems after an acquisition and show combined data within a couple of weeks. 16. Dina describes the current system as able to answer questions in about a second and a half and says the earlier IBM Watson version cost about $5 to generate a million words, while the current AWS-based version costs about half a cent. 17. Dina and Anthony sound relaxed and practical, with Anthony pushing on user experience, workflow, and time savings. 18. The format is an interview with detailed back-and-forth, and Dina repeatedly returns to customer experience, plain English output, and decision speed. 19. Best for business leaders, product teams, and enterprise AI buyers. 20. Skip it if you want consumer AI stories or high-level hype.

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