Delivers a better product experience with Elastic
With Elasticsearch, Fiber AI's product searches and unifies information across key data sources to create signal-based audiences in seconds that customers can use for highly targeted sales outreach.
Boosts customer outreach yield by 50%
With Elasticsearch's AI search features, Fiber AI has helped their customers increase the yield of prospects that are targetable for outreach by 40-50%, allowing customers to build a more extensive sales pipeline.
Reduces data costs by 80% even after growing database to terabytes
With Elastic's data tiering capabilities, Fiber AI optimized and scaled its growing database and reduced monthly costs by more than 80% without affecting performance and response times.
Super accurate and highly scalable, Elasticsearch enables Fiber AI customers to automate prospecting workflows, set up meetings, and close deals with fewer resources
Fiber AI is a top Y Combinator backed startup revolutionizing the way organizations target and engage with sales prospects worldwide. Aditya Agashe and Neel Methta were selected for Forbes 30 under 30, under the Marketing & Advertising Class of 2024, for starting Fiber AI, an AI-powered sales automation platform that enables customers to streamline outbound sales and prospecting workflows. Elasticsearch, built on the powerful Search AI Platform, plays a critical role at the heart of this solution.
Used by Sales Development Representatives (SDRs) and Business Development Representatives (BDRs), Fiber AI enables customers to search through its database to find target prospects with unparalleled accuracy, send custom messages drafted by generative AI, and automate other key sales activities.
As a result, sales and business development teams can spend less time on manual tasks and more time building relationships. This increased focus has enabled Fiber AI to scale to over $1M in Annual Recurring Revenue (ARR) in less than 6 months after launch, by securing deals with notable companies like Ramp, Docusign, Flatfile, Lumos, Secureframe, and more.
A billion rows searched in a second
Although still an early Y Combinator backed startup, Fiber AI stands out for its massive prospecting database, aggregating data from over 50 providers, including BuiltWith, Crunchbase, and G2. It also boasts the largest offline LinkedIn database, containing 13 million+ global job postings, data on 40 million+ companies worldwide, and 850 million+ LinkedIn profiles.
Making this massive volume of data easily searchable is a huge undertaking. When building its infrastructure, Fiber AI evaluated several database search solutions, including ClickHouse and other columnar databases. The team even experimented with SQL solutions that use vectorization techniques on PostgreSQL. However, none matched the speed and performance of Elasticsearch.
Neel Mehta, CTO and founder, Fiber AI, says, “When I first tried Elasticsearch, I was blown away. I ran a search on a billion rows in just one second, whereas other products took 30 minutes. I honestly don’t know how we managed without it.”
Elasticsearch’s agility also enables Fiber AI to quickly add new search criteria in response to customer needs. For instance, a new customer requested a feature to find employees at companies with five to 10 personnel holding the title of product manager and based in India.
Neel Mehta says, "I was really worried, thinking it would take months to build and require additional hires for ETL (Extract, Transform, and Load), multiple databases, joins, and more."
To his surprise, it required only a few 100 lines of Elasticsearch DSL (Domain Specific Language) code. "No other tool I know has increased our productivity like Elasticsearch. It allows us to add new features for our customers every week. The amount of time and effort it saves is enormous," he says.
With Elastic, Fiber AI is able to build a better product experience, enabling its customers to take advantage of search features that accelerate deal generation.
From startup to scale-up
As a company with a small, eight-person team, Adi Agashe, CEO and Founder, Fiber AI, found scaling up daunting. "We started with just a few gigabytes of data, and now we have dozens of terabytes stored monthly," he says. "I thought, there's no way a small team can handle this."
Elasticsearch has been critical in overcoming those challenges. "We began testing with about a million rows, and now we're handling a billion without any noticeable slowdown." He also highlights Elasticsearch's efficiency with inverted indices: "No matter how much data you throw in, Elasticsearch runs just as fast," he says.
Elasticsearch also excels in standardizing job titles when searching offline LinkedIn data. For example, someone searching for an engineering manager might encounter variations such as 'engineering manager,' 'E.M.,' or 'manager, engineering,' and potentially in multiple languages.
Fiber AI has integrated hundreds of synonyms into its system, allowing customization of terms and stop words. For instance, if a customer searches for 'rev ops,' it automatically recognizes this as 'revenue operations.'
Greater precision enables Fiber AI customers to find high-quality prospects faster. "Our customers no longer waste two to three hours compiling lists of job titles manually," says Neel Mehta. "They don't have to rely on broad, vague search terms that yield long lists of mediocre prospects and often lengthy vetting processes."
"With Elasticsearch, customers have increased their sales outreach response rates by 40 to 50% with virtually no loss in performance."
A speedy response to support tickets
Adi Agashe also praises Elastic's support team. “Elastic was one of the first companies we worked with where senior principal engineers jumped on calls with us whenever we had a support ticket open,” he says.
For example, Elastic advised the Fiber AI team on optimizing their Elasticsearch setup, including hot/warm tier strategies and cluster configurations. This led to a significant cost reduction of over 80%, decreasing monthly costs from mid 5-figures a month to sub $10,000 a month.
With Elastic's support, Fiber AI plans to scale its AI capabilities and add further automation features for customers within their product. With the ability to integrate Elastic and its AI capabilities into the product, Fiber AI is innovating faster than ever. "We're working on providing quick auto-responses that include meeting links, FAQs, or whatever else the customer needs," Aditya Agashe says. "With Elastic, we can continue to scale up our AI capabilities and keep adding new search features."
