While AI agents are increasingly capable of solving customer support problems, most people can still tell immediately when they’re talking to a machine instead of a human.

Smallest.ai, a startup founded in late 2024, is betting the next leap in voice agents will not come from making large language models faster, but from using smaller, specialized models built for human conversation. Simply put, the company wants to make speaking to an AI agent indistinguishable from talking to a human.

To do so, it’s developing a small voice model designed to mimic how humans process information by listening, thinking, and speaking simultaneously.

“While I’m speaking to you, you’re already thinking, and you might interrupt me if I talk for too long,” Sudarshan Kamath (pictured left), founder and CEO of Smallest.ai, told TechCrunch, adding that this is exactly how the startup’s model is designed to work.

To fuel this mission, Smallest.ai has raised $13 million in a Series A round, led by Seligman Ventures with participation from Sierra Ventures and 3one4 Capital. The fresh capital brings the startup’s total funding to over $21 million.

“The way an LLM works is you give it an entire prompt, and then it starts thinking,” Kamath said. While that latency is acceptable in a text chat, in a voice conversation, even a short pause feels unnatural. “If you think about how we are talking, I’m not giving you like a large clipping of my audio, and then you start thinking.”

The startup’s model serves as a real-time intelligence layer that enables natural customer conversations on specific topics, with virtually zero response lag. But if the model encounters a subject outside its limited knowledge base, Smallest.ai hands off the query to a large foundational model, briefly placing the customer on hold to “research” the issue—just as a real human would do.

Kamath believes that all AI agents will soon rely on two models: a small voice model for real-time interaction, and an “offline” LLM that is called upon as needed to solve complex problems.

Unlike large foundational models, Smallest.ai focuses strictly on voice-specific nuances, such as handling diverse accents, supporting dozens of languages, and operating in noisy environments.

The startup’s existing customers include companies in the voice space, including RingCentral and Truecaller. Kamath said that any customer support company, including newer ones like Sierra and Decagon, is a potential customer for the startup.  

When asked why a well-funded AI customer support company wouldn’t build its own voice model, Kamath said that for customer support startups, becoming “extremely good at doing voice is a distraction from their core business.”

Smallest.ai competes with voice AI leader ElevenLabs, as well as Cartesia and regional players like Sarvam that focus on local languages.

While some competitors apply voice AI to use cases, like audio dubbing and podcasting, Smallest.ai focuses strictly on real-time conversational voice agents for its enterprise customers.

“We want our models to break the Turing test,” Kamath said. “You should speak to our model and not know it’s AI or human. That’s the sole focus of the company.”

During Meta’s Q2 2026 earnings call, Mark Zuckerberg said that other revenue in the family of apps segment crossed $1 billion, largely thanks to WhatsApp paid messaging and subscriptions.

As more businesses use WhatsApp to reach consumers, users’ inboxes often get cluttered, making it hard to find personal and group messages. Meta is now trying out a new feature where it will place messages from larger businesses like banks or airlines in a separate folder, TechCrunch has learned exclusively.

When a user receives a message from a large business, WhatsApp will automatically move that message to a new “Offers & Updates” folder after a set number of hours. The company said it is testing different durations, up to 24 hours, to move messages to a new folder.

Users who prefer their messages to be on the timeline can turn this setting off. However, they don’t control when messages are moved automatically.

Meta said that with this feature, messages like discount codes and delivery updates are out of the inbox in a few hours, and the main chat timeline feels less cluttered. For businesses, this means that users can look for their messages in a specific folder rather than getting lost in all chats.

WhatsApp is starting to test this feature with select partners using its WhatsApp Business Platform, and will look to expand based on observations. At the moment, small businesses and individual accounts using WhatsApp Business are exempt from this feature. WhatsApp said it could explore moving business messages from small businesses to the new “Offers & Updates” folder in the future.

In the last few years, WhatsApp has taken steps to reduce business message spam. In 2024, it started allowing users to unsubscribe from marketing messages from brands. Last year, it put a curb on the number of broadcast messages businesses and individuals can send in a timeframe. In October 2025, it went one step further and limited the number of messages businesses could send without getting a response from users. The company has fully rolled out the first two features while it is still iterating on the third feature.

Despite these steps, WhatsApp inbox can feel chaotic. From my own experience, there have been days when I have cleared unread messages at the start of the day only to end with more than 30-40 unread messages. Even at the time of writing, more than half of my unread messages were business communications. I am not alone in feeling this.

The new feature might reduce the clutter a little, but it won’t be effective until users have controls over filtering out messages from the main inbox.

WhatsApp made its AI business agents available globally in June, with more than 1 million businesses already using them. During the earnings call, Zuckerberg mentioned Brazil’s car rental company Movida and said that it has seen an uptick in conversions and customer support issue handling through AI agents. In the coming months, we could see more businesses use AI within WhatsApp for sales, marketing, and support use cases. A chat app with over 3 billion users must strike a balance between personal and business messages before it becomes a vehicle for AI spam.

Given a rising number of publishing misconduct allegations, IEEE in 2022 created the Publishing Ethics Team as a centralized department to assist in handling claims. The group also works to increase the organization’s visibility in the broader publishing ethics area and helps IEEE volunteers write new policies.

Here are some highlights of the team’s activities last year.

New detection tools

IEEE conducted a pilot program in 2024 to integrate tools from the International Association of Scientific, Technical, and Medical Publishers (STM) Integrity Hub into the peer-review workflow of IEEE Access. The multidisciplinary, fully gold-open-access journal publishes research results across all IEEE fields of interest.

STM created the hub so scholarly publishers could access a suite of integrated, commercial, third-party research integrity tools as well as those developed by STM Solutions. The tools help the publishing group avoid printing problematic content upon manuscript receipt, rather than reacting postpublication.

The new features include the Clear Skies Papermill Alarm, which helps identify potentially fraudulent manuscripts at submission. Another is an integration with the PubPeer database, which allows users to check whether references in a manuscript have received previous PubPeer comments or have been retracted—both of which can indicate quality or integrity issues. The duplicate submissions detector can determine whether the same manuscript has been submitted to multiple journals by different publishers, often a sign of academic “paper mill” activity.

Following the success of the pilot, IEEE began working last year to expand the services to all its periodicals. It is anticipated that all IEEE periodicals will be included in the Integrity Hub screening by the end of this year.

Raising visibility

The team participated in industry-wide initiatives with STM. It also renewed membership in groups including the Committee on Publication Ethics, and the team continued its work sponsoring and presenting at conferences.

At a panel presentation during the Council of Science Editors annual meeting last year, Amanda Sulicz, manager of IEEE Research Integrity, participated in the Research Integrity Investigation panel session. She also presented at the Standardization of Publishing Integrity Norms and Corrective Actions poster session during the Society for Scholarly Publishing’s annual meeting, held 28 to 30 May 2025.

Luigi Longobardi, the IEEE Publishing Ethics and Conduct director, gave a presentation at the Communication and Collaboration With Institutions session during STM Innovation and Integrity Days, which took place 9 and 10 December.

IEEE was a sponsor of the National Conference on Research Integrity, held 20 to 22 May 2025, and the International Congress on Peer Review and Scientific Publication, held 3 to 5 September.

Ethics reports

The team is responsible for tracking ethics-related complaints for all IEEE publications, including articles published in periodicals and conference proceedings. When complaints regarding an article’s integrity are received, either via email at pub-ethics@ieee.org or the anonymous ethics reporting line, the team works with IEEE volunteers to open a case, investigate the complaint, and resolve the matter.

Last year 591 cases were opened, a 56 percent increase over 2024. Of the 591 reports, 317 were closed and 274 are still under investigation. Of the complaints, 88 percent were research-related, including issues with plagiarism, AI-generated text, and falsification of—or unauthorized use of—data. The other 12 percent involved alleged misconduct by editors, reviewers, and conference organizers.

The complexity of the reported cases has expanded. An increasing number of the complaints deal with more than one article or complicated situations such as editorial misconduct or peer-review manipulation.

Conference publications

For the second consecutive year, the team participated in the joint IEEE Publication Services and Products Board/IEEE Conferences Committee’s ad hoc committee on conference publication quality. The committee is tasked with analyzing and reviewing problematic conference papers and enhancing quality screening of articles prior to publication to detect integrity issues such as plagiarism and tortured phrases. The committee also updates educational modules on organizing and managing conferences.

As part of the review process, the committee focused on conference articles that contained tortured phrases, which are nonstandard English expressions that are imprecise or erroneous and give the impression of technical jargon.

Many of the articles reviewed by the ad hoc committee were identified by the Problematic Paper Screener, a free online tool that uses application programming interfaces to screen papers published online for potentially problematic content, such as tortured phrases, machine-generated content (SCIgen or Mathgen, for example), or references to retracted content.

The ad hoc committee was responsible for reviewing and recommending the retraction of more than 1,700 problematic conference articles last year.

Case studies

From the cases the team reviewed, IEEE learned valuable information to help update its publishing policies and best practices.

Here are examples of two anonymized cases reported to the team last year.