Krisp nearly triples fundraise with $9M expansion after blockbuster 2020

The rise in virtual meetings — often in noisy places like, you know, homes — has led to significant uptake across multiple industries. Krisp now has more than 1,200 enterprise customers, Baghdasaryan said: banks, HR platforms, law firms, call centers — anyone who benefits from having a clear voice on the line (“I guess any company qualifies,” he added). Enterprise-oriented controls like provisioning and central administration have been added to make it easier to integrate.

Image Credits: Krisp

B2B revenue recently eclipsed B2C; the latter was likely popularized by Krisp’s inclusion as an option in popular gaming (and increasingly beyond) chat app Discord, though of course users of a free app being given a bonus product for free aren’t always big converters to “pro” tiers of a product.

But the company hasn’t been standing still, either. While it began with a simple feature set (turning background noise on and off, basically) Krisp has made many upgrades to both its product and infrastructure.

Noise cancellation for high-fidelity voice channels makes the software useful for podcasters and streamers, and acoustic correction (removing room echos) simplifies those setups quite a bit as well. Considering the amount of people doing this and the fact that they’re often willing to pay, this could be a significant source of income.

The company plans to add cross-service call recording and analysis; since it sits between the system’s sound drivers and the application, Krisp can easily save the audio and other useful metadata (How often did person A talk versus person B? What office locations are noisiest?). And the addition of voice cancellation — other people’s voices, that is — could be a huge benefit for people who work, or anticipate returning to work, in crowded offices and call centers.

Part of Krisp’s allure is the ability to run locally and securely on many platforms with very low overhead. But companies with machine learning-based products can stagnate quickly if they don’t improve their infrastructure or build more efficient training flows — Lengoo, for instance, is taking on giants in the translation industry with better training as more or less its main advantage.

Krisp has been optimizing and reoptimizing its algorithms to run efficiently on both Intel and ARM architectures, and decided to roll out its own servers for training its models instead of renting from the usual suspects.

“AWS, Azure and Google Cloud turned out to be too expensive,” Baghdasaryan said. “We have invested in building a data center with Nvidia’s latest A100s in them. This will make our experimentation faster, which is crucial for ML companies.”

Baghdasaryan was also emphatic in his satisfaction with the team in Armenia, where he and his co-founder Arto Minasyan are from, and where the company has focused its hiring, including the 25-strong research team. “By the end of 2021 it will be a 45-member team, all in Armenia,” he said. “We are super happy with the math, physics and engineering talent pool there.”

The funding amounts to $14 million if you combine the two disparate parts of the A round, the latter of which was agreed to just three months after the first. That’s a lot of money, of course, but may seem relatively modest for a company with a thousand enterprise customers and revenue growing by more than 2,000% year over year.

Baghdasaryan said they just weren’t ready to take on a whole B round, with all that involves. They do plan a new fundraise later this year when they’ve reached $15 million ARR, a goal that seems perfectly reasonable given their current charts.

Of course startups with this kind of growth tend to get snapped up by larger concerns, but despite a few offers Baghdasaryan says he’s in it for the long haul — and a multibillion dollar market.

The rush to embrace the new virtual work economy may have spurred Krisp’s growth spurt, but it’s clear that neither the company nor the environment that let it thrive are going anywhere.