8 Best AI Data Analytics Software & Tools of 2024
Is AI The Future Of Search? A Deep Dive Into Innovation With A Leader In The Field
Share
Share
Share
Search technology has never been more important. With Google processing 99,000 searches per second and enterprises generating 2.5 quintillion bytes of data every day, businesses across industries are scrambling to make sense of an overwhelming influx of information. At the heart of this challenge is AI-powered search, which is quickly becoming the go-to solution for organizations looking to unlock the full potential of their data. In fact, the global AI-powered search market is projected to reach $10.7 billion by 2027, growing at a CAGR of 23.6%.
In this fast-evolving landscape, where companies race to stay ahead, Sujan Abraham stands out as a thought leader. With over 10+ years of experience in developing cutting-edge AI and search solutions, Sujan's contributions have not only shaped the future of enterprise search but have also made meaningful advancements in how we interact with information. But as AI technology continues to accelerate, Sujan poses a critical question: Is AI the future of search?
A Career Built on Search InnovationSujan's journey into the world of software engineering didn't follow the traditional path. After earning a degree in Mechanical Engineering from Kerala University, he self-taught programming languages, and his natural curiosity led him into software. "I've always been drawn to solving problems," Sujan shares. "Search, in particular, fascinated me because it's all about making information accessible in a meaningful way."
That fascination became his life's work. Sujan's career took off when he joined Citrix India in 2012, where he worked on GoToMyPC, a remote desktop solution, and eventually transitioned to the ShareFile platform. It was at Citrix where his passion for search technology blossomed. He led efforts to enhance search capabilities, creating more intuitive, faster, and efficient systems that helped companies manage and retrieve critical files.
His contributions didn't stop there. At Better.Com, Sujan led the development of search solutions for the real estate sector. "We were trying to simplify something complex—homeownership," he says. "The challenge was to create a search tool that would empower users by showing them the right options, faster, and more accurately."
Pushing the Limits at LabelboxIn his current role at Labelbox, Sujan's innovation took a quantum leap. As a senior software engineer, he's responsible for building AI-powered search engines capable of natural language processing and similarity search. His team developed a scalable ingestion platform that processes data 10 times faster, making the entire search process smoother and more effective. "AI isn't just improving search," Sujan explains, "It's redefining how we understand and interact with information."
The key, Sujan points out, is to create systems that "think" like users, anticipating their needs and delivering results in a way that feels seamless. His recent work with vector embeddings and AI-driven natural language search allows users to make more intuitive, conversational queries rather than relying on keyword-heavy searches. "The future is about making search feel human," he says. "We're moving away from rigid, machine-like searches to something much more fluid and dynamic."
The Story of Addoo: An Entrepreneurial SpiritOne of Sujan's most notable innovations came during his time in the Raleigh Innovators Program. There, he co-founded Addoo, a customer onboarding platform designed to personalize the onboarding process for new users. "With Addoo, we saw an opportunity to make the customer experience simpler and more effective," Sujan recalls. "The platform could tailor itself to the user's needs, helping them navigate a product without the need for customer support."
Addoo was widely successful within Citrix, significantly improving user engagement and reducing the workload for customer success managers. Citrix even offered to spin Addoo out as a standalone company, with the product integrated into several of its SaaS offerings. "It was a validation of what we were doing," says Sujan. "It showed that if you focus on solving real problems, you can make a huge impact."
The Role of AI in Shaping the Future of SearchWhen asked about the role of AI in the future of search, Sujan is optimistic but grounded. "AI is undoubtedly the future, but we're just scratching the surface of what's possible," he says. "The real breakthrough will come when AI can not only understand what you're searching for but why you're searching for it. That's when search becomes truly transformative."
Sujan sees a future where AI-driven search engines are integral to all industries, from real estate and healthcare to media and entertainment. "We're already seeing AI enhance the user experience, but the next step is building systems that learn and adapt in real time," he explains. His work at Labelbox is setting the foundation for this next generation of search technology, with the integration of machine learning models that can evolve alongside user behavior.
A Mentor and InnovatorOutside of his technical achievements, Sujan is also a thought leader and mentor in the AI and search community. He frequently judges research papers and hackathons, with his latest appearance last week at HackMIT as an Expert Judge. "It's incredibly rewarding to see what the next generation of engineers is working on," he says. "Innovation comes from collaboration and community. That's something I'm deeply passionate about."
As Sujan looks to the future, he is eager to continue pushing the boundaries of what's possible in AI and search. "The beauty of search is that it's always evolving," he reflects. "We're constantly learning how to make it better, faster, and smarter. And AI is a big part of that evolution."
Optimizing Shopping Ads For Natural Language Search
Google still makes up the lion's share of all search traffic, which makes Google Ads a critical investment for brands and retailers. But if you want to optimize your ad spend and reach your goals, you need to enrich your product details and incorporate the language and trend insights your customers use.
This playbook outlines how brands can optimize ad performance by incorporating customer-centric, high-performance attributes like:
Download your copy and start operationalizing natural language search to see a 25% boost in sales in just three weeks.
The Google Ads Playbook: How To Operationalize Natural Language Search To Optimize Ad Performance
Google still makes up the lion's share of all search traffic, which makes Google Ads a critical investment for brands and retailers. But if you want to optimize your ad spend and reach your goals, you need to enrich your product details and incorporate the language and trend insights your customers use.
This playbook outlines how brands can optimize ad performance by incorporating customer-centric, high-performance attributes like:
Download your copy and start operationalizing natural language search to see a 25% boost in sales in just three weeks.
Comments
Post a Comment