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Synthflow picks up $7.4M for no-code voice assistance for SMEs

What is AI good for? Automating repetitive tasks for the very busy people running small businesses, reckons Berlin-based startup Synthflow, which is announcing a $7.4 million seed round for its SME-focused no-code platform for AI voice assistance.

Since being founded around spring last year, the startup has now banked a total of $9.1 million, underscoring ongoing investor enthusiasm for accelerating applications of generative AI.

The startup also claims to be approaching 1,000 customers — touting “double-digit” monthly growth rates since it stepped out of stealthy development to launch its browser-based “no code” tool in December 2023. That suggests there’s a healthy appetite among SMEs to adopt — or at least experiment with — generative AI tools that promise easy-to-reach productivity gains.

The new funding will be plowed into R&D, according to Synthflow CEO and co-founder Hakob Astabatsyan, who says the team is keen to keep stoking its early momentum by increasing product utility and broadening the scope of SMEs to which it’s appealing.

“We have very many ideas. We know exactly what the customers need,” he tells TechCrunch.

Astabatsyan, a serial entrepreneur with a business background, is ex-Rocket Internet. Joining him in his latest venture are his brother, Albert, who also worked with him on a prior no-code startup; and Sassun Mirzakhan-Saky, who brings a software engineering background and CTO expertise to the team.

While Synthflow’s product kicked off with English-language call handling because its largest markets are English-speaking, it has since added German and French language versions (note: these are still in beta). So dialing up its focus on the latter markets in Europe is also on the cards.

End-to-end experience

Call centers were early adopters of AI voice agents, pulling on the APIs of large language models (LLMs) to power systems that could answer phone calls in a human-like way — just with indefatigable energy and enthusiasm 24/7, if not always flawless comprehension.

Synthflow is taking the concept in a slightly different direction, targeting service industry-focused SMEs directly, including those towards the smaller end of the category with a DIY “no code” offering. The goal is to offer SMEs an “end-to-end” experience, per Astabatsyan, who argues that the return on investment from being able to automate core tasks like appointment scheduling will be immediately obvious to its target resource-strapped businesses.

“The AI can do it in a more affordable manner, more reliably, and humans can do other stuff,” is his concise pitch for voice assistance.

He gives the example of a handyman or mechanic who would typically answer the phone themselves when not working on a job — meaning they inevitably end up missing a lot of calls and losing out on some business as a result; or a dentist who employs a receptionist who works limited hours so, again, isn’t always around to pick up the phone.

Having a tool that can handle basic customer inquiries could be a game changer for small businesses, Astabatsyan argues.

Synthflow’s target being SMEs necessarily means a core focus for the startup is making AI technology accessible to non-technical users — which is why it’s built a no-code interface for its customers to design voice agents that fit the needs of their businesses.

“We wanted to try to build something simple,” he explains. “A no code layer on top [of AI agents] so that … business owners, business oriented people, can go and play around with this and get familiar and explore what the LLMs can do for their businesses.”

Synthflow’s interface lets customers drag and drop elements to configure voice AIs that can perform specific tasks for them — such as scheduling appointments, running through FAQs, or performing “information extraction,” such as obtaining personal information from a potential customer so a human can call them back.

Image Credits: Synthflow

“Let’s say if someone has to call, and there is a particular set of questions to be asked and particular pieces of information to be collected — especially static ones, such as, address, home, etc. — AI is very good,” he argues.

The customer can choose to configure the AI assistant so it discloses it’s a robot. “I think it is very good practice to disclose that it is a virtual assistant,” says Astabatsyan. “My personal favorite opening is: ‘Hello. My name is [so-and-so], right now, all our lines are busy. I apologize for that. I am the virtual assistant here at [the name of the business]. How can I help you?’”

Another big utility for voice AIs is recognizing when a call needs to be transferred to a human agent, according to Astabatsyan. So, essentially, using AI to filter inbound calls based on complexity — with automation taking care of the simple requests, which then compounds the benefit by freeing up human agents to have more time to spend on more complex customer inquiries.

He stresses the goal isn’t to replace human jobs but rather suggests AI can help SMEs be more productive and efficient than they could otherwise be with their limited resources.

This is why, as well as letting customers deploy voice agents, Synthflow’s system is designed to take care of post-call data entry tasks too — adding appointments to a calendar tool for instance. Building out integrations with third-party software is thus another big focus for the team.

“This is what the AI is so good at,” he argues. “Because it can take this information [extracted from a call] and, let’s say, update particular fields in particular CRM — and if you do these things at scale, on hundreds or thousands of calls, suddenly we’re seeing this technology advantage that we saw [when businesses first adopted] computers.”

For the voice agents, the startup is building on OpenAI’s GPT LLM but also incorporating its own AI models on top — which Astabatsyan says have been trained on its own data and fine-tuned to specific customer use cases.

He says it has also built its own “voice orchestration layer,” which converts the customer’s speech into text that can then be fed to the AI model as a prompt, returning an automated answer that the system converts from text into speech the customer hears as a synthesized voice on the other end of the phone line.

For now, Synthflow is focused on using AI with inbound calls — which Astabatsyan suggests are the low-hanging fruit for automation for resource-strapped businesses. But he hints at more sophisticated capabilities in development, with R&D fueled by the chunky seed round.

One thing he mentions they’re working on is a feature that will enable Synthflow’s voice AIs to perform what he refers to as “live actions” or “connections” — meaning that during a call the AI would be able to run a check on live inventory in a warehouse. Or pull in another other piece of requested info and “push it elsewhere,” as he puts it.

He also sketches a scenario where task-focused AI voice systems would be able to expand their utility collectively. They could hand off a call to other dedicated voice AIs trained for different tasks being requested by the customer.

“The key here is to have focus on who your customers are. Because, depending for whom you are building this, your product is going to be very, very, very different,” he adds.

One impact to consider is, if voice AIs and voice assistance systems live up to the productivity hype — slickly delivering on the promise of efficiently handling a whole layer of customer enquiries, including by expertly redirecting more complex stuff to the right system or human to deal with — it could end up meaning the average SME discovers they have an awful lot more work than they’re able to take on.

“I think that’s an interesting question for a lot of managers and leaders to think about, right?” he responds, discussing this scenario. “Like, if there’s so much capacity — and productivity gets unleashed — how do we channel this human resources in other sectors of the economy? Because I think this question is not answered yet, but it’s a very interesting question indeed.”

Synthflow’s seed funding is led by Singular, with participation from existing investor Atlantic Labs and a number of investors in the AI space, including the founders of Krisp AI.

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