For decades, the relationship between humans and machines has been defined by a single, frustrating constraint: we have had to learn the language of software to get anything done. Whether it is navigating nested menus, memorizing keywords, or fighting through rigid phone trees, the burden of adaptation has always been on us.

At Stochastic, we believe the era of the manual interface is over. We are building the future of the intelligent interface: autonomous, multimodal voice agents that adapt to humans, not the other way around.

The Vision: Moving Beyond the "Digital Tool"

Our team has spent years building the processors that power how machines see, hear, and understand. Glenn Ko, our founder, led work across Samsung, IBM, Qualcomm, and Harvard on the underlying hardware that enables modern AI.

A pattern kept showing up.

Even as systems got faster and more capable, people were still doing the same work around them. Hunting for the right field. Copying reference numbers from one system to another. Explaining the same issue over voice, email, and chat to different teams.

Every major leap in computing came from a change in interface, not just more compute:

• Command line to graphical interfaces

• Desktop to mobile, mouse/keyboard to touch

• Mobile to always-on voice and notifications

The current implementation of the manual interface is still far from ideal. People still spend hours clicking through portals, filling out forms, searching across different systems, and repeating themselves on every call and channel. The machine has gotten faster, yet the way we work with it has hardly changed. Even recent advances in AI often result in "chatbots" that remain static, waiting for a prompt and delivering text that someone still has to act upon.

You can feel the hidden cost of a bad interface in the numbers. Knowledge workers commonly lose more than an hour a day just navigating systems, searching for information, and coordinating across teams. Frontline staff, like call center agents or clinic coordinators, can juggle five to ten systems during a single interaction.

In healthcare, administrative overhead has grown into hundreds of billions of dollars per year. Much of that is not core care. It is people doing work for the systems rather than systems working for the people.

To remove this friction, we envision a more advanced form of human-machine interface, the Thinking Agents. They move beyond simple inputs to Multimodal Intelligence. These agents don't just read text; they see, listen, and understand the physical world in real time. They possess the autonomy to not only suggest work but to orchestrate and execute it in the background, acting as a true digital extension of a human team.

What is a Thinking Agent?

A Thinking Agent is an AI system that acts like an always available teammate, not a one-off chatbot.

At a high level, it has three key abilities:

1. Memory
   It remembers what matters at three levels. The organization, the team, and the individual. This includes your terminology, your policies, your typical resolutions, and the details of ongoing cases or tasks.

2. Reasoning
   It can take a real-world request, break it into steps, and decide what to do next. This often means coordinating different tools, handling exceptions, and knowing when to escalate to a human.

3. Guardrails It operates within clear boundaries. It respects privacy, follows compliance rules, and has clear conditions where it asks for help instead of guessing.

These abilities are powered by our Agent Computer, the platform that combines memory, reasoning, and guardrails into one controllable system. It connects to the channels you already use, such as phone, chat, SMS, and email, and to the systems where your work happens, such as EMRs, CRMs, ticketing tools, and document stores.

Voice is the Next Frontier of Multimodal Interface

Voice is the most natural way humans communicate, yet it remains the most underdeveloped modality in the enterprise. Why? Because "Voice" is incredibly hard to get right. It is not just about transcribing words (Speech-to-Text). It is about Voice Reasoning: understanding tone, detecting pauses, handling interruptions, and maintaining context in a noisy environment.

Members of Stochastic have spent decades solving the technical challenges of machine perception. Our architecture is built for extreme low latency. While legacy systems often suffer from a "laggy" two-second delay that kills conversational flow, our agents operate at human speed, making the interaction feel fluid and natural.

First Stop: Solving the Healthcare Crisis

We are starting where the friction is highest: Healthcare Administration. 

The US spends over $1 trillion annually on administrative overhead. While doctors and nurses are stretched thin, a massive amount of labor is trapped in "operator tasks," scheduling, patient intake, and managing information flow.

Consider a healthcare setting, such as a clinical operations team supporting patients, providers, and staff.

Traditionally, a patient call can involve:

• Pulling up the right record in the EMR

• Checking recent notes and prior authorizations

• Looking at scheduling rules and insurance details

• Updating forms or sending follow-up messages

Each step often lives in a different tab or system. The staff member spends much of the call navigating software, not actually helping the patient.

With a Thinking agent in place, the experience is different.

The agent listens, understands the request, and handles the routine steps across systems. It handles the "arms and legs" of healthcare admin, connecting to external apps, processing unstructured documents, and managing patient communications autonomously. It brings the right information into view and takes on repetitive updates. 

The human staff member is no longer acting as a bridge between systems. The Thinking agent is. Such a switch specializes the agent in repetitive bridging tasks, in which it is more consistent than a human being. At the same time, human staff members can focus on the human parts of the interaction. One clinical operations leader put it simply: 

“I expected automation to make our processes faster. I did not expect it to improve consistency and reduce administrative burden this much.”

The Path Forward

Since our first healthcare agent pilot in January 2025, we have moved rapidly from building core infrastructure to deploying production-ready reasoning agents. The future of work shouldn't be spent clicking buttons. It should be spent communicating, and at Stochastic, we’re building the machines that finally listen.