VoiceRun raises $5.5M to build voice agent factory giving developers control over AI voice agents

VoiceRun nabs $5.5M to build voice agent factory | TechCrunch

Nicholas Leonard and Derek Caneja wanted to build AI voice agents, but when they went to build the product, they felt many of these voice agents had design flaws. Some of these agents were being built with no-code tools, meaning shipping to production was fast, but the quality of the product was often low. Other agents were being made by companies that had the time and resources to spend months building specialized tools. "Developers and enterprises needed an alternative," Leonard told TechCrunch, adding that he and Caneja also realized that the future of software would be "coded, validated, and optimized by coding agents." "These two insights and a historical realization gave us the inspiration for VoiceRun," Leonard, the company's CEO, said. Caneja is the company's CTO. Last year, they decided to launch VoiceRun, a platform that lets developers and coding assistants launch and scale voice agents. Right now, many of these low-code platforms let people build voice agents with visual diagrams, where people click through conversation flows and write prompts into boxes that then dictate how the agent should behave. All of that can be hard to manage, Leonard said. VoiceRun, on the other hand, lets users code how they want their voice agents to behave, giving them more flexibility in creating the product they want. Code is the native language of coding agents, Leonard explained. "They are going to do a far better job operating in code than in a visual interface," Leonard said. Furthermore, with visuals, there are limited configuration options, so, for example, if someone wanted to build a voice agent that could speak in a different dialect, it might be harder to do if the maker of the visual interface didn't build a feature that can handle that task. "But in code, it's incredibly simple to do," he said. "There is a long tail of millions of examples of little things you might want to do that aren't supported by the visual interface." Aside from coding agents, VoiceRun also lets users perform A/B testing and deploy instantly with one click. The company is geared toward enterprise developers, helping companies, for example, incorporate AI into their customer services, or help tech companies launch voice-based products. He mentioned, for example, working with a restaurant-tech company launching an AI phone concierge for food reservations. The company announced on Wednesday the closing of a $5.5 million seed round led by Flybridge Capital. There is a lot of competition in the AI agent space. Startups in this area last year nabbed billions of dollars (out of the many billions that flooded into AI companies in general). Leonard feels his company is up against two ends of the market: There are the no-code voice builders, like Bland and ReTell AI, he said, that lets user build quick demos. There are also more sophisticated tools, like LiveKt and Pipecat, which give developers "maximum control." He feels Voicerun sits in the middle of these two ends. "We provide global voice infrastructure and an evaluation-driven lifecycle, while keeping ownership of business logic code and data in the customer's hands," he said. "The key difference is that we are closing the loop for end-to-end coding agent development. We expect developers to be supervising coding agents that write code, run tests, deploy, and propose improvements." In some ways, Leonard is hoping his product helps developers create voice agent tools that will, in turn, help people feel more comfortable with automated voices. Customers today "feel relief" when a human answers the phone, "because voice automation has been brittle and ineffective." A survey from Five9 last year showed that three-fourths of its survey respondents still prefer talking to a human when it comes to customer service matters. Leonard said he wants to change this perception because "human agents today have their own limitations," like language barriers or making people feel judged. "There were great cars before the Model T, but vehicles didn't become ubiquitous until the assembly line," Leonard said. "There are great voice agents today, but they won't be ubiquitous until the voice agent factory is built. VoiceRun is that factory."

VoiceRun gets $5.5M in seed funding to give enterprises more control over voice AI agents - SiliconANGLE

VoiceRun gets $5.5M in seed funding to give enterprises more control over voice AI agents VoiceRun, a startup that's helping enterprises to develop voice-enabled artificial intelligence agents that they control, has raised $5.5 million in seed funding to help customers move beyond simple pilots and demonstrations and deploy voice-powered applications at large scale. Today's round was led by Flybridge Capital Partners and saw participation from RRE Ventures and Link Ventures. VoiceRun said the funds will be used to boost its go-to-market efforts as it gears up its platform for prime time. VoiceRun's main pitch is helping enterprises to develop voice AI agents that meet the strictest of reliability, security and governance requirements, which it says is essential for organizations seeking to deploy them in production. It does this through a novel code-first approach and forward-deployed engineering model that allows technical teams to ship voice AI agents rapidly without giving up control of them. With its platform, customers retain full ownership of their application layer code, while VoiceRun provides the orchestration layer they need to leverage third-party large language models to power those apps. It also provides tools for turn-taking, telephony and latency management, so customers can continuously assess their voice applications, iterate and improve them over time. The startup, which is targeting voice AI applications in industries including restaurants, insurance, banking and telecommunications, says there are three core components to its platform. The first is the infrastructure and orchestration layer, which uses pluggable LLM, speech-to-text and text-to-speech pipelines, interruptible prompts and one-click telephony to enable enterprises to piece together voice agents using third-party models. These are all accessed via standard Git or command line workflows, which allows teams able to integrate internal APIs, transform data and complex model logic. Finally, it provides a library of enterprise-grade tools, including LLM-as-a-judge evaluations, telemetry and synthetic data generation for regression testing and targeted model enhancements. With these tools, companies can quickly identify where their AI agents need improvement. Crucially, VoiceRun also offers flexible deployment options, including public cloud environments, virtual private clouds and on-premises, to meet its customer's data and compliance requirements. Early customer rollouts span phone ordering and reservations, contact center triage, and lead qualification. These are use cases where milliseconds matter and organizational controls often slow adoption. VoiceRun's deployment flexibility, including VPC options and approved model lists, allows enterprises to work within existing security and compliance requirements while still shipping new voice experiences. VoiceRun co-founder and Chief Executive Nick Leonard said AI chatbots such as Gemini, which can converse with users in the same way as if they were talking to another human, highlight the enormous potential of automated, voice AI agents in areas such as customer service. A lot of companies have already created impressive pilot projects, but very few have been able to ramp them up into full production deployments, he said. "Many enterprise projects stall between an impressive demo and a dependable production rollout," he explained. "We give teams code ownership, deployment flexibility and deep observability so they can move fast, clear security reviews and deliver production-ready solutions at scale." Flybridge Capital Partners co-founder Chip Hazard said it's fast becoming clear that voice is going to be the preferred interface for many AI applications because of the convenience it offers to users. "Bringing these applications into production presents a paralyzing build-versus-buy decision," he said. "VoiceRun offers the missing piece which empowers enterprises to build, govern and scale world-class voice deployments."