AI investment is predicted to hit $2.5T in 2026, but it still hasn’t hit the bottom line. 

Nine in ten organizations already use AI in at least one business function, but almost 80% of those same companies report no material impact on profitability. McKinsey calls this the “gen AI paradox.” The explanation is fairly straightforward: the AI that has scaled is mostly for desk work: productivity tools, document summarization, code assistance, knowledge search. These spread quickly, but their gains have not broadly shown up in earnings.

Meanwhile, the business functions with the greatest economic potential, those that generate and protect revenue, are still looking for the right solutions. This includes high-volume commerce, frontline and physical operations, employee-facing service desks, and customer service, among others.

That’s because they’re the ones running in real time, at scale, with the least margin for error. In that environment, a resolved interaction is a retained customer or immediate revenue, while a breakdown is a measurable loss. General-purpose AI alone can’t handle the real world conditions they require.

At SoundHound AI, we built OASYS to deliver conversational AI agents that work for your customers and employees in the real world.

Sources: McKinsey State of AI 2025; Gartner CS Leader Survey 2025; Puzzel State of Contact Centres 2026

Introducing OASYS

OASYS, the Orchestrated Agent System, is a voice-native conversational AI platform for building AI agents that talk to customers, resolve complex service issues, process transactions, assist sales teams, and more – reliably at scale.

The platform is designed for the teams responsible for a conversational AI interface to generate revenue, drive retention, and define customer experience at scale across every channel their customers and employees use. 

What makes it different

Most function-specific AI deployments stall for similar reasons: voice that breaks down in noisy environments, agents that can’t handle sensitive tasks reliably, deployments that only work in limited channels, AI that can’t handle transactions or exceptions, and build cycles that take too long. 

OASYS addresses each, and shifts how operational teams work.

When AI is reliably handling authorizations, routine transactions, and common service requests head-on, teams stop being reactive and start being strategic, by shifting their focus to oversight, experience improvement, and work they simply didn’t have capacity for before.

Voice-Native AI

OASYS is built on our foundational speech recognition model and doesn’t rely on third-party integrations. It processes audio in a single step, handles interruptions and mid-conversation language switches, and holds up in noisy environments where standard models fail. For any interaction that happens in person, over a phone, through a speaker, or in a physical space, this is the foundation that makes everything else possible.

AI Builds AI and Continuous Learning

Deploying enterprise AI has historically meant months of configuration and specialist resources. With OASYS, teams can simply feed the platform their existing interaction data, transcripts, training materials, or process documentation and it generates fully configured agents ready for review.

Once live, those agents improve themselves every day. OASYS analyzes every interaction at the agent level and proposes its own optimizations to the team daily, so performance improves quickly. Teams can move faster and leaner, while restructuring how they approach automation management and optimization.

Agentic+: A Resolution Framework

The biggest barrier to deploying AI in high-stakes functions isn’t typically capability, but reliability. OASYS agents combine autonomous reasoning with rule-based guardrails and our unique human resolution layer.

For example, if an AI interaction hits a wall, a human can intervene in the background to steer it to resolution in real time without escalation or a terminated chat. AI agents finish what they start, containment rates improve dramatically, and enterprise brands get the control they need to put AI where the margin for error is low.

“Before, the AI platform couldn’t adjust to changes on the fly. Now, it’s flexible. It can proceed without information in sequence, circle back, and engage customers fluidly — just as a human agent would.”

Juan Carlos Chávez Cureño
Director of Claims Customer Service at Quálitas

Advanced QA & Testing 

Most enterprise AI deployments go live with limited visibility into how agents will behave under real-world conditions. OASYS includes an AI-driven simulation and testing environment that lets teams stress-test agents before pilot or production. This surfaces edge cases, and validates performance against key metrics before a single live customer is affected. The result is faster deployment cycles with significantly less risk, and a clearer picture of where an agent is ready and where it still needs work.

Commerce Ecosystem

Most AI agents are contained in the browser, but operational departments often aren’t. Especially those that interact with customers every day. OASYS deploys across phone, chat, kiosk, drive-thru, smart device, connected vehicle, and custom hardware — all from a single platform. Build agents once, and deploy them anywhere your customers are.

Deploy Everywhere: Digital & Physical

OASYS agents are designed to function as revenue generators. With branded agents handling transactions with OASYS, they’re joining a connected commerce network where their products can be discovered and purchased across millions of third-party interfaces. Your AI agents don’t just serve your customers and employees. They become a new revenue source.

Using OASYS in the real world

While the applications of OASYS are broad, we’ll highlight a few examples where its AI agents can do their best work across various operational functions:

• A dispute leads to a sale — An OASYS agent resolves a billing dispute autonomously, then surfaces a personalized upgrade offer at the optimal moment, turning a service cost into a revenue moment.

• In-car commerce on the go — A driver confirms their usual coffee order with voice input. Payment processes before they arrive for pick-up, without a button click.

• Real time sales assist on the retail floor — An ambient agent observes a live sales conversation in a wireless store, and surfaces the best fit bundle to the associate’s earpiece mid-conversation. 

• Outbound retention at scale — OASYS detects churn signals through a Customer Data Platform integration, and initiates a personalized voice conversation before the customer potentially cancels, with no manual human dialing.

• Prescription refills without a queue — A patient requests a refill by voice. The OASYS agent verifies identity through an Electronic Health Record, checks eligibility, and confirms with the pharmacy for pick up. Fully automated, in under a minute.

• IT service desk without the backlog — Employees resolve access requests, troubleshooting, and maintenance issues through a voice or chat agent in minutes, so your most important people stay unblocked. 

• Drive-thru ordering — A voice agent takes a full order in a noisy environment, handles modifications, and completes an upsell faster and more accurately than a traditional POS interaction.

Twenty years in the making

At SoundHound, we have spent two decades building, deploying, and learning from voice AI in production. We’ve built for brands like Hyundai, Chipotle, and GoDaddy across contact centers, storefronts, vehicles, restaurants, and more. That history is embedded in the platform. 

The proprietary models behind OASYS were trained on real interactions at scale, in conditions that take years to accumulate. And the agentic orchestration, human-in-the-loop capability, contact center intelligence, and voice commerce infrastructure natively embedded in the platform today each came from teams that spent years solving those specific problems for large enterprises.

What does that mean for a business deploying OASYS? The platform comes with a team that has already worked through the hard problems. And continues to, with every interaction we handle.