Boston-based voice intelligence company Modulate has secured $25 million in fresh funding for its platform, which leverages a collection of small models to provide enterprises with transcription, emotional analysis, deepfake and AI music detection, and policy enforcement for voice agents operating in regulated industries.

This investment aligns with a broader trend among investors in the expanding voice AI sector: supporting companies that aim to make AI-generated voices sound more human. Modulate also competes with firms working to detect intent in human conversations through analysis, as well as those focused on protecting individuals and organizations from deepfake calls—a growing concern given how easy voice cloning has become.

The new funding round was led by Future Ventures, with participation from Hyperplane and Lakestar. According to PitchBook data, the startup had previously raised $41 million at a $170 million valuation before this round.

Founded in 2017 by Mike Pappas and Carter Huffman, who met as MIT physics undergraduates, Modulate initially focused on voice modulation for gaming. Over time, it shifted toward a voice-based moderation tool. With the rise of voice AI models, the company now concentrates on detecting various types of AI audio generation and analyzing the intent behind a person's words.

Today, the company operates over 100 models, broadly divided into two categories: signal extraction models that interpret vocal emotion, tone, language, and synthetic voice determination; and analysis/detection models that assess intent—such as what a customer is trying to communicate, whether a caller is breaking rules, or whether they are attempting to scam the recipient.

Huffman noted that because Modulate runs smaller models, it doesn't require specialized hardware or massive compute resources—an advantage that could prove critical as token costs rise. Additionally, it's easier for the company to train models with new capabilities, add them to the roster, and have an orchestrator invoke them as needed.

Modulate serves a diverse customer base but specializes in deepfake detection and alerting organizations like call centers to potential scams. It also monitors how AI agents respond to customers to evaluate call quality and ensure AI adheres to compliance rules in regulated sectors. Because of these offerings, Modulate often operates alongside a company's existing voice stack, purely to analyze calls.

As more enterprises adopt AI-powered customer service, understanding why a customer call succeeded or failed becomes increasingly important. In this context, gauging customer intent and response goes beyond basic analysis. Huffman said Modulate can provide enterprises with granular data on this front.

"I think when companies think of emotion analysis, they think if the customer was neutral or positive, the call was a success, and if the customer was negative, the call was a failure. But actually, many times people will be polite even to, like, AI agents or bots. Right. And they won't come across as angry, but they'll be very dissatisfied," he said.

The company also stated that its technology is being used to monitor cyberattacks conducted through voice calls. Modulate currently employs 40-45 people and plans to add 10 more in the coming months to strengthen model development. The startup is also working on expanding its on-premises and on-device deployment capabilities to enhance privacy.