Insent.ai, which offers a business-to-business enterprise sales platform, has raised $2 million from Emergent Ventures in a seed-level funding round. Insent plans to use the funds to expand its data visibility and automated chatbot integrations.
The Seattle-based company was founded in 2018 and operates within the conversational sales and marketing space for mostly SaaS clients.
Founder Arjun Pillai told VentureBeat his team built the platform’s data capabilities around potential enterprise use cases. “The use case was very clear. But [deciding] what technology would help us to get there was obviously a very challenging decision,” he said.
Pillai said his tech team played with high-volume data and held conversations with external CEOs and CPOs to flesh out the platform’s data strategy. This involved looking into what kinds of data they used and didn’t use, whether they were self-hosting data or using AWS, what their cost-scaling looked like, and if they had constructed that scaling in-house or with an external service. After filling in this picture, Insent started to experiment.
“So we put together a bunch of data,” Pillai explained. “And then we ran really high-volume stress tests on some of the architects’ thinking, like 300 million records over … and we looked at how MongoDB, for example, scaled. And is it crashing?” The Insent team then put assumptions in place for the stress test and projected where the company might be between 36 and 54 months out and what scale of data it might be dealing with at that time. “Everything that we have built is probably looking at five to six years ahead of us. At that point, we know, there is probably a little bit of re-architecting that we may have to do,” Pillai added.
Insent’s platform is hosted on AWS and uses MongoDB for its database. Pillai said Insent chose MongoDB because it’s a NoSQL, or non-relational database. MongoDB lacks the arrangement tables SQL has, and Pillai claimed that until recently, NoSQL options didn’t have the technical capabilities to support the scale that companies like Insent required. But now, he explained, NoSQL choices can scale with speed.
“Between all our customers, we sync the data every 20 minutes or so,” he said. “And now, when we expand to 1,500 or 2,000 customers, we are talking about billions of data points getting updated. This was not possible 10 years back on a NoSQL database, but today it is.” He added that the system is performing super fast because of MongoDB.
Another major decision, according to Pillai, was flipping from lead-based architecture to account-based architecture on the database level. He said Insent is focused on account-based orchestration, which lets individuals from one company be added as leads and grouped as an account at the same time, helping boost clients’ B2B sales productivity.
“So the architecture is obviously manually decided. But as far as the scaling is concerned, it is all automated,” he said. “There are enough database services that will enable us to run automated services of scaling up and scaling down … to make sure that when you are sleeping, if a customer connects a 10 million [record] database, the system scales up.”
Pillai also described how Insent uses JavaScript for tracking and processing visitor data for the API to edit chatbot conversations in real time, using integrations with external data providers like Sixth Sense. He said when Insent gets a visitor and doesn’t know who it is, “we go and task six cents through an API,” he said. “We take that data and we do further processing of that data. All of this happens in microseconds. Basically, the moment somebody lands on the website, boom, the API call comes back with the data based on that website, company visitor.” Pillai suggested this tracking is akin to what Google Analytics and Marketo do.
According to materials Insent provided VentureBeat, in addition to broadly expanding its chatbot integrations and data visibility, the startup is looking to split its new funds between developing the engineering, sales, and marketing teams, in that order. Insent also wants to help distinguish prospects from customers with better visitor data intelligence. Insent claims this identification will help personalize interactions by handling cookie data across multiple enterprise systems.
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