NEW YORK--Nicholas Dessaigne, founder and CEO of Algolia kicked off the monthly Data-Driven meetup last May 19 at AXA Center by talking about the journey of his company in delivering a great search experience for apps and websites with its hosted search API.
Today, Algolia has 1,500 enterprise customers with 36 data centers in 15 regions, serving billions of queries weekly in under 50 ms for more than 1300 customers, including many Fortune 500 companies.
Algolia is scalable and reliable, with a 99.99% SLA and both server and provider redundancy.
In his presentation, Dessaignee talked about its journey through the years since it was founded in 2012. He recalled ow in March 2015, the company spread its US clusters across two completely different providers
Algolia is designed from the ground up to maximize the speed of search and solve the pain of relevance tuning. It pushes the search experience beyond its traditional limits for better user engagement.
“Building an HA architecture takes time. Design early (but) do not over-engineer,” he said. “Focus on execution.”
“You have to be as upfront as you can. Definitely do a post-mortem and why it should not happen again.
Louis DiModugno, chief data and analytics officer at AXA US (global leader in insurance), talked about how the company is enhancing customer experience and making sure it has the right balance of products to protect them.
DiModugno knows data can’t flow freely, so it maintains data offices in Paris, US and in process of building one in Singapore. “We are a young company,” he said, announcing job openings for engineers in the coming weeks.
6Sense is a B2B predictive intelligence engine for marketing and sales.
Amanda Kahlow, founder and CEO of 6Sense, says it’s “all about timing” as she addressed the number one thing CMOs and sales both want to know: “when buyers are in market.”
“We accelerate sales by finding buyers at every stage of the funnel,” she said.
Founder and CEO Peter Brodsky said HyperScience (AI for the enterprise) leverages a novel approach to AI to automate work currently performed by human data scientists, solving the pain points across the enterprise.
“We identify subnets.” Subnets can be used in different applications.”
He demonstrated how it works by asking people to upload photos of images he listed on the projector screen where people then tweeted them and HyperScience identified correctly.
“Most databases can only tell you about the past. HyperScience can tell you about the future,” he said.
Requiring no data science or statistics, it seems. It is self-configuring, self-tuning and self-healing. It scales horizontally and supports real time queries.