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Hyro, an adaptive communications company that offers plug-and-play AI assistants for enterprises, today announced it has raised $20 million in a series B funding round.
The company said it will use the round — which was led by Macquarie Capital — to hire across departments and build out its offering for conversational and generative AI-driven call centers, websites or mobile applications. It will also expand strategic partnerships, integrations and use cases across key industries.
The funding comes as enterprise interest in AI for streamlining business functions and end-user experiences continues to soar. In a recent survey conducted by Accenture, 98% of global executives agreed that AI foundation models will play an important role in their organization’s strategies in the next 3 to 5 years. Hyro plans to capitalize on this.
How does Hyro’s AI help?
Founded in 2018, Hyro offers an enterprise platform that provides plug-and-play tools to help companies implement a layer of conversational AI assistants on top of their existing omnichannel workflows without any kind of coding.
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“Hyro’s key differentiator is our ability to come to the first meeting with a prospect and show them a fully functional AI assistant built on their own data, without them needing to do anything at all,” Hyro’s VP of marketing Aaron Bours tells VentureBeat. “Assistants that usually take 6-12 months to build (based on predefined intents, data training and ML) are ready to launch pending procurement, and that excites enterprise buyers who have been previously underwhelmed by chatbot companies.”
![Hyro product](https://venturebeat.com/wp-content/uploads/2023/05/Hyro-Product.jpeg?w=800&is-pending-load=1#038;resize=558%2C297&strip=all)
Once an enterprise points Hyro towards a business logic it wants to achieve and its internal knowledge, the platform automatically scrapes unstructured and structured data and maps it to a knowledge graph with all the different entities and attributes already embedded, made queryable by natural language (through voice or text). Then, using this graph, it generates a conversational AI assistant that can be embedded across channels like websites, mobile apps, call centers and more.
“When the content updates, the conversations update — that’s where we avoid maintenance/ IT resource deployment usually associated with NLP/NLU solutions,” Bours explained.
Deployment in three days
Hyro claims it can deliver AI assistants in a matter of three days with text and chat capabilities. It primarily focuses on the information-heavy healthcare industry, serving providers like Mercy Health, Baptist Health and Intermountain Healthcare, with AI agents automating tasks like patient registration, routing, scheduling, FAQs, IT helpdesk ticketing and prescription refills.
This makes up roughly 60 to 70% of inbound calls and messages into health systems, the company said.
Moreover, the AI assistants provided by Hyro are also paired with conversational intelligence, where organizations get an out-of-the-box dashboard to see performance engagement metrics, top trends, keywords, missing terms and explainability surrounding AI outputs.
These reports are auto-generated, promoting full visibility and a constant feedback loop for optimization.
How Hyro is planning ahead
With this round (which takes Hyro’s total capital raised to $35 million), the company will build out its platform for the healthcare industry and focus on expanding with new strategic partnerships and more in-depth integrations with key CRMs and telephony systems.
On the product side, the company will continue to refine NLU rates and upgrade the conversational intelligence capabilities of the platform with real-time alerts, upgrades and benchmarking. It will also invest in capturing more granular data points that allow for stronger reporting of trending topics, keywords and more.
“For example, we can tell enterprises that they may be in for a spike in traffic for a certain service before it happens,” Bours explained.
In addition to doubling down on the healthcare space, Hyro also intends to deploy go-to-market efforts and resources towards other highly-regulated industries like insurance, as these will also need explainable AI assistants to field repetitive calls and messages in light of growing workforce shortages.
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