Talkdesk, a customer experience software company, announced Monday a set of new tools designed to help organizations manage artificial intelligence and human agents as a single, coordinated workforce — addressing what the company describes as a growing accountability gap in how enterprises deploy AI in customer service.

The release centers on two products: a new CXA Operations Center, which provides centralized monitoring and governance of AI agents in live production environments, and enhanced capabilities within Talkdesk’s existing Interaction and Quality Analytics platform, which links conversational data to business outcomes and helps identify where automation can be most effectively deployed.

The Problem Talkdesk Is Trying to Solve

As AI handles a growing share of customer interactions, most organizations are still measuring its performance using tools and metrics built for human-only workforces, the company said. That mismatch, Talkdesk argues, leaves leaders without the visibility needed to scale AI responsibly or understand how the introduction of AI agents is reshaping the work that falls to their human counterparts.

When AI absorbs routine interactions, the conversations that reach human agents tend to be more complex — which can inflate traditional efficiency metrics like average handle time even as overall service quality improves. Without a unified view of both workforces, that dynamic is easy to misread.

Also Read: Your Rebrand Is Failing. Have You Tried Listening?

What the New Tools Do

The CXA Operations Center is built around two core capabilities. AI Agent Observability gives teams real-time insight into how their AI agents behave in production: monitoring live activity, analyzing session-level execution traces and diagnosing failures through detailed error inspection. AI Agent Evaluation allows teams to measure agent behavior across scenarios, compare versions against defined performance benchmarks, and catch unintended changes before or after deployment.

The updated Interaction and Quality Analytics platform adds two new features. CX Insights moves beyond static dashboards to surface which specific interactions are affecting key performance metrics and links them to concrete improvement opportunities. Automation Mining uses process analysis to identify high-impact automation candidates within existing customer interactions, and lets organizations model the projected impact of automation before committing to deployment.

Tiago Paiva, chief executive and founder of Talkdesk, said: “As AI agents handle more customer interactions, they must be managed like any other employee — trained, tested and held accountable. When AI takes the simple tasks, human agents focus on the complex ones. This might increase average handle time, but it is because those conversations are more valuable. Leaders can no longer look at these groups in silos. We are helping companies manage human and AI agents side by side, as one team, to deliver great customer experiences together.”

The post Talkdesk Unveils Tools to Manage AI and Human Agents Together appeared first on MartechView.

For years, AI in retail was framed as an efficiency play: better inventory forecasting, smarter demand planning, faster ticket resolution. It was about reducing costs, shaving seconds off handle times, and streamlining back-end systems.

That era is over.

Today, AI sits much closer to the revenue engine. It influences how customers discover products, how they interact with brands, how issues are resolved, and, increasingly, whether they return. In retail, travel, and hospitality, where loyalty is fragile and competition is relentless, customer experience is no longer a support function; it is a core function. It is a strategy.

Few executives have observed that shift from both the operational and technological sides as closely as Michael Klein, Director of Retail, Travel & Hospitality Product Marketing at Talkdesk. Before moving into enterprise CX technology, Klein spent more than three decades in retail merchandising and leadership roles, including time with Adobe and Williams-Sonoma.

That background, he says, fundamentally shapes how he evaluates enterprise software.

“I’ve spent more than three decades in retail,” Klein said. “My background in retail merchandising keeps me focused on how technology actually improves the customer experience and drives real business outcomes. It’s never been about leveraging technology just for the sake of it.”

In merchandising, every decision — from assortment planning to store layout — is tied to measurable results. Klein brings that same lens to AI.

“AI is a strong example,” he said. “When applied well, it helps increase average order value, drive repeat purchases and improve retention.”

In other words, the question is not whether AI is impressive. It is whether it sells more sweaters, books more rooms, or deepens loyalty.

“At Talkdesk, we’re focused on using it where it truly makes a difference for retailers and their customers,” he added.

The Persistent Myth of the Demographic Customer

Retailers have more customer data than ever before. Yet, paradoxically, many still design experiences around broad assumptions.

“One of the biggest misconceptions is that everyone in a demographic bucket behaves the same way,” Klein said. “That Gen X shops one way, Millennials another, and Baby Boomers another.”

The reality, he argues, is messier.

“If it were that clean, personalization would be easy,” he said. “But I’ve seen plenty of Baby Boomers who are perfectly comfortable booking travel online and plenty of younger customers who want to speak to a person when something goes wrong.”

The mistake, he suggests, is building customer journeys around stereotypes rather than behavior. Digital-first consumers are not defined by age alone; they are defined by context, urgency, and preference at any given moment.

Designing around assumptions creates friction. Designing around actual signals creates loyalty.

From Cost Center to Growth Engine

Perhaps the most profound shift underway is the redefinition of the contact center.

For decades, contact centers were treated as overhead — necessary to resolve complaints, but disconnected from growth. AI is changing that calculus.

“From a customer standpoint, AI makes it easier to self-service when they want to,” Klein said. “That convenience drives satisfaction — and satisfied customers tend to spend more.”

Self-service is not about removing human interaction; it is about giving customers control. When done well, automation reduces frustration and accelerates resolution.

For brands, the internal impact is just as significant.

“AI frees up contact center teams to focus on higher-value work,” Klein said. “Whether that’s helping design a room, building a wardrobe, or solving a complex issue. Those are real revenue-driving conversations.”

By removing friction in knowledge access, documentation, and agent training, AI shifts human effort toward consultative interactions — the kinds of conversations that build trust and increase basket size.

At its best, automation does not replace people. It elevates them.

Why So Much “AI-Powered CX” Falls Flat

In a market saturated with “AI-powered” claims, differentiation often dissolves into jargon. Klein has spent years translating complex enterprise technology into language retailers actually understand — and he is blunt about what works.

“Great marketing and complex jargon just don’t mix,” he said. “Instead of relying on technical words that only developers or product managers use, brands should drop the IT acronyms and language that’s too deep in the weeds.”

Retailers do not buy platforms. They buy outcomes.

Plain language, he argues, forces vendors to clarify their value proposition. If a product cannot be explained without abstraction, it likely lacks practical grounding.

Separating Real AI From Marketing Noise

Klein is equally pragmatic about the current AI moment. Not all AI is new — and not all of it is transformative.

“We first need to be clear about which AI we’re talking about,” he said.

Retailers have long used predictive models to forecast inventory, optimize distribution, and manage replenishment. Those systems quietly shape customer satisfaction by ensuring products are in stock.

“That has a direct impact on product availability and customer satisfaction,” Klein noted.

More recently, generative and agentic AI have begun to deliver tangible value in marketing and service environments — drafting content, assisting agent,s and streamlining workflows.

Where the narrative drifts into hype, he says, is in the idea of full automation.

“We’re a long way from AI taking over everything,” Klein said. “Human oversight still matters, and consumers will want the choice between automation and a real person depending on the situation.”

The future, in his view, is hybrid — not robotic.

The Context Problem

If there is one area where brands consistently misstep, it is context.

With so much data available, companies often mistake volume for insight.

“The key to designing better experiences is relying on context signals, like timing and intent, coupled with history and preference,” Klein said.

Without context, personalization becomes misdirection. A customer who once purchased a gift for a relative may be permanently misclassified, leading to irrelevant recommendations.

“Imagine you visit a store for the first time to buy a present for your grandmother,” he said. “If the retailer caters your experience based only on your first visit, your experience won’t serve your current needs.”

The difference between intelligent personalization and awkward irrelevance often comes down to whether brands understand why a purchase occurred — not just that it did.

The Hardest Part of Modernization

Enterprise modernization is rarely blocked by technology alone.

“The biggest hurdle brands encounter is not doing anything for fear of disrupting operations,” Klein said.

Legacy systems may be aging, but they are stable. Change introduces uncertainty.

“The next hurdle is weeding out bad data,” he added. “And the third is dealing with people who are stuck in their old ways or too protective of their territory.”

Transformation demands both technical cleanup and cultural shift. It requires encouraging teams to experiment, test openly, and share ownership across departments.

Without that alignment, even the best technology stalls.

The Metrics That Will Matter Next

As AI becomes embedded in CX systems, traditional metrics such as handle time and surface-level satisfaction scores may lose their primacy.

“In the next few years, customer lifetime value, recency, and frequency will become key metrics to monitor,” Klein said, particularly in retail and hospitality.

Those measures capture relationship strength rather than transaction speed. They reflect whether AI is driving durable loyalty rather than short-term efficiency.

In that sense, the next phase of AI in customer experience is not about the volume of automation or technological sophistication. It is about commercial impact.

For Klein, that is the through line connecting his merchandising past to his product marketing present. Technology is not the hero of the story. The customer is.

And in a competitive landscape where switching costs are low and expectations are high, the brands that treat customer experience as a growth lever—not a service line item—will be the ones that endure.

The post Retail’s AI Reckoning Is About Revenue — Not Robots appeared first on MartechView.

Artificial intelligence is everywhere in customer experience—or so the marketing claims. Yet beneath the buzzwords and glossy demos, many enterprises are discovering that “AI-powered transformation” often looks suspiciously like old workflows with new labels.

In this conversation, Kevin McNulty, Senior Director of Product Marketing at Talkdesk, cuts through the hype to examine what’s actually changing—and what isn’t. From the limits of single-agent AI to the overlooked importance of data architecture, McNulty offers a grounded view of how AI is reshaping customer service, marketing, and trust itself—and why the next phase of CX will be defined less by automation and more by orchestration.

Excerpts from the interview; 

What’s the most overhyped belief about AI-powered customer experience that enterprises need to abandon?

The most overhyped belief is that a single AI bot can solve complex customer experience challenges simply by being added to an existing workflow. Many organizations assume that plugging in an AI model will somehow create transformational change. In reality, that approach delivers only marginal gains.

True transformation happens when companies move away from isolated AI models performing narrow tasks and toward multi-agent orchestration frameworks. In those environments, AI systems can reason together, coordinate actions, and execute end-to-end outcomes. If your operating model still depends on humans stitching together fragmented workflows, you’re not transforming customer experience—you’re merely augmenting it.

At Talkdesk, we think about AI not as a feature but as a workforce. And like any workforce, AI requires structure, orchestration, governance, and shared context. Once organizations start thinking this way, they also begin to recognize the need for quality management—setting standards, measuring performance, and ensuring accountability. That shift in mindset is where real transformation begins.

Many brands claim they’re moving CX from a cost center to a growth driver, yet their operating models still resemble 2015. What’s the structural barrier holding the industry back?

It comes down to data fragmentation.

Enterprises have invested billions in digital transformation, but customer data remains scattered across CRMs, ticketing platforms, policy systems, and even individual agent desktops. You simply cannot drive a growth-oriented customer experience if your AI lacks a unified, trustworthy understanding of the customer.

There’s also an uncomfortable truth the industry doesn’t like to acknowledge: AI cannot fix bad data. In fact, generative AI that retrieves the wrong information with great confidence is worse than no AI at all. The solution isn’t to keep layering intelligence on top of broken systems—it’s to fix the underlying information architecture first. Only then can organizations unlock meaningful value from AI.

As AI systems take on more of the customer journey, how should brands design experiences for a world where AI intermediaries increasingly act on behalf of customers?

The first requirement is a common language. If AI agents are going to interact with other AI agents, they need shared protocols and governed, traceable knowledge. We’re starting to see early standards—things like agent-to-agent frameworks—emerge, but we’re still at the beginning.

From a design standpoint, this requires a fundamental shift. When AI agents act on behalf of customers, you’re no longer designing linear journeys. Agents can move faster, multitask, and adapt dynamically, which means experience design becomes less about scripting flows and more about defining decision frameworks.

Humans follow scripts. AI agents follow policies, context, rules, and constraints. That’s what designers need to focus on building.

Another critical concept is outcome unification. Behind the scenes, AI-to-AI interactions will become incredibly complex, involving multiple systems and agents collaborating simultaneously. But from the customer’s perspective, the experience must feel seamless. Even if five agents contributed to an answer, the customer should receive a single resolution, a single narrative, and a coherent outcome—without contradiction.

You’ve argued that humans won’t be replaced anytime soon. Where should AI take the lead in customer service to force the industry to evolve?

Knowledge management is the most logical place for AI to lead.

In customer service, the biggest bottleneck is rarely agent capability or staffing levels. It’s that organizations don’t truly understand or manage what they already know. Knowledge is scattered across call transcripts, internal documents, policy files, and historical interactions—and it’s often outdated the moment it’s documented.

AI can transform knowledge into a living, governed system. It can continuously structure unstructured data, surface gaps, keep content fresh, and proactively suggest improvements.

Take the airline industry as an example. A rare policy question may already have been answered once—buried inside a 15-minute call transcript. AI can surface that answer, formalize it, and ensure the next customer receives an instant response instead of repeating a long, frustrating interaction. That’s where AI can dramatically improve both efficiency and experience.

Industries like insurance are rapidly deploying AI agents at scale. When does efficiency begin to erode trust—and how should companies manage that risk?

Trust erodes the moment AI becomes opaque or unaccountable.

There’s enormous pressure to automate, and that pressure can push organizations to deploy AI beyond what their data quality, governance, or policies can support. Our advice is straightforward: autonomy must match data quality. If your data is incomplete or unreliable, your AI should not be fully autonomous.

Explainability must also be non-negotiable, especially in regulated industries like healthcare and financial services. Customers need to understand when they’re interacting with AI and how decisions are being made. Transparency is essential to maintaining trust.

Human-in-the-loop systems are not a crutch—they’re a safety net. The best AI systems escalate intelligently, not because they’re confused, but because they recognize when confidence drops. Responsible automation has to be designed from the beginning. It cannot be retrofitted after something goes wrong.

What three shifts will define marketing and martech in 2026—and why should brands pay attention?

The first shift will be the rise of agentic website experiences, which will begin to replace traditional SEO as the primary discovery model. Websites will no longer rely on navigation or keyword-driven search as their main entry point. Instead, AI agents will guide visitors through conversations. That fundamentally changes digital marketing—fewer page views, more interactions, and a shift from optimizing for keywords to structuring knowledge for machines.

The second shift is the convergence of the marketing stack and the contact center stack. Historically, marketing has owned the top of the funnel while contact centers managed post-purchase interactions. AI collapses that divide. The same data, knowledge, and workflows can power both, enabling far more automation and continuity across the customer journey.

The third shift is outcome-based pricing. As AI adoption accelerates, organizations want clear proof of value. Pricing models will move away from seats and licenses toward outcomes delivered—tasks completed, issues resolved, value created. That will fundamentally change how ROI is defined and how technology investments are justified.

Every year brings a buzzword. What’s the most overhyped promise in marketing right now—and what’s the reality behind it?

The most overhyped promise is the idea of an all-in-one AI agent that can manage the entire customer journey with a single prompt.

The customer journey is inherently complex. It involves identity verification, intake, troubleshooting, compliance, updates, and personalization—often across multiple channels. A single AI agent cannot reason across all those domains with the level of accuracy and specialization customers expect. It will either oversimplify, hallucinate, or fail when it encounters nuance.

The reality is that effective customer experience requires a team of specialized AI agents, each focused on a specific capability, coordinated by an orchestrator that manages conflicts and unifies outcomes. One agent solving everything is a compelling story—but it’s not a realistic one.

For marketers entering an AI-driven era, what’s one piece of advice to stay relevant in 2026 and beyond?

Break the rules.

We’re at the very beginning of this AI era, and this is the moment to rethink everything. Don’t limit yourself to how marketing worked in the past. Younger marketers, in particular, aren’t burdened by legacy assumptions—and that’s a strength.

Imagine the experiences you’d want as a customer. We’ve all used tools like ChatGPT or Claude. Think about what feels intuitive, helpful, and human—and then think about how to build that. You no longer need deep coding expertise to experiment and create.

Marketing success will increasingly be measured by outcomes, not clicks or forms. Challenge assumptions. Break existing workflows. Invent new ones. This moment feels as transformative as the early days of the internet, and it’s moving just as fast.

There’s a natural instinct to fear AI, just as there was fear when the internet emerged. But history shows that these shifts don’t eliminate opportunity—they expand it. The marketers and brands who lean in early will help define what the future looks like.

The post Human-in-the-Loop Isn’t a Crutch. It’s the Safety Net. appeared first on MartechView.

Talkdesk®, Inc. announced the expansion of its partnership with Databricks, the Data and AI company. Talkdesk has selected Databricks to power the data foundation for its Customer Experience Automation (CXA) platform, accelerating the future of responsible, artificial intelligence (AI)-driven customer engagement through its Built on Databricks Partner Program. 

Traditional customer service data often sits scattered across contact center as a service (CCaaS), customer relationship management (CRM), and enterprise resource planning (ERP) systems. This makes it challenging to scale data pipelines or manage compliance for large, unstructured interaction datasets. The Talkdesk and Databricks partnership addresses this by delivering:

• Unified intelligence: Talkdesk CXA AI Agents get real-time access to the full customer history across all channels through zero-copy integration with customer data.

• Smarter automation: Rich, contextual data allows Talkdesk AI Agents to provide personalized, accurate, and adaptive responses.

• Trusted AI foundation: The solution is built on a governed, enterprise-grade infrastructure that helps meet compliance, security, and explainability standards.

“Through this partnership, we are giving enterprise customers a safe, scalable way to deploy AI that truly transforms how businesses service their customers. Integrating the Databricks Data Intelligence Platform with Talkdesk’s CXA platform gives companies 360° visibility into customer interactions, fueling more intelligent automation and analytics. This allows them to build responsibly and meet compliance and transparency standards from the start, at an accelerated pace,” said Munil Shah, chief technology officer of Talkdesk.

Talkdesk CXA, announced in June 2025, automates and coordinates complex service, sales, and support processes from the front office through the back office. Instead of layering more tools into an already complex customer experience stack, Talkdesk CXA replaces fragmented, manually coordinated workflows with a unified system of intelligent, autonomous AI agents. Each AI agent has a defined role and shared context, working together in real time to resolve complex issues across front- and back-office functions — enabling faster, more precise automation at scale. 

The Databricks Data Intelligence Platform democratizes access to analytics and intelligent applications by marrying customers’ data with powerful AI models tuned to the unique characteristics of their business. The platform is built on a lakehouse architecture of open data formats and open governance to ensure that all data is completely within the customers’ control.

Also Read: Edition 3: Sharp Minds Decoding Tech’s Next Wave

“Customer interaction data is incredibly valuable, but too often it’s fragmented or duplicated across systems. With the Databricks Data Intelligence Platform, Talkdesk Customer Experience Automation can securely access that data in place — no replication required — to deliver faster, more accurate, and fully-governed customer experiences at scale,” said Heather Akuiyibo, vice president of go-to-market integration at Databricks.

More information about Talkdesk CXA can be found here.

The post Talkdesk Expands AI Partnership with Databricks appeared first on MartechView.

Talkdesk®, Inc. today introduced Talkdesk AI Agents for Insurance, a new suite of intelligent automation capabilities purpose-built to help insurers streamline operations, strengthen compliance, and enhance customer and employee experiences across the policy and claims lifecycle. Built on the Talkdesk Customer Experience Automation (CXA) platform, AI Agents for Insurance combines agentic AI and multi-agent orchestration to automate and manage complex workflows — from coverage validation and First Notice of Loss (FNOL) to checking on claim status, upcoming bill payment, and getting a new quote. 

Insurers face rising claim volumes, regulatory pressure, and growing expectations for immediacy and transparency. Yet legacy, fragmented systems and manual processes often result in slow, costly, and inconsistent experiences. Talkdesk AI Agents for Insurance overcomes these challenges with pre-built AI agents for insurance-specific workflows, no-code configuration for rapid deployment, and seamless integration with policy administration, claims management, billing management, and customer relationship management (CRM) systems that accelerate time to value.

Moving beyond isolated automations, multi-agent orchestration coordinates both AI and human agents across departments and systems to complete end-to-end workflows quickly and accurately, at scale. This intelligent, collaborative approach results in straight-through processing for many high-frequency, standard cases, reduced manual effort and rework, and improved consistency and quality of interactions. 

Also Read: Tariffs Test How Much Price Pain Shoppers Can Take

For example, when a policyholder reports an auto accident, coordinated AI agents can verify identity, assess fraud risk, collect claim details, and generate a complete claim record for adjuster review—managing in minutes what once required multiple handoffs across departments.

“The launch of this unified platform represents the next evolution of intelligent insurance operations,” said Tiago Paiva, chief executive officer and founder of Talkdesk. “By pairing secure agentic AI with multi-agent orchestration, Talkdesk is helping insurers drive operational efficiency and cost reduction while delivering the kind of responsive, empathetic service that builds lifelong policyholder trust.”

Key capabilities include:

• Human-like self-service for diverse communities: 24/7 multilingual automation for policy information, payments, and claims intake across voice and digital channels.

• Employee empowerment: Real-time Copilot guidance, continuous context sharing between agents, automated QA, and AI-powered knowledge surfacing help adjusters and agents make faster, more compliant decisions with less manual effort.

• Autonomous operations: Specialized AI agents orchestrate policy, claims, billing, and compliance workflows using context and data from systems like Guidewire, Duck Creek, and Salesforce.

• Expedited payment collection and increased sales: Proactive outbound engagement helps payment collection by notifying customers of upcoming or past-due payments. This strategy also generates higher revenue by delivering marketing product offers across a variety of channels.

• Built-in compliance and governance: Enterprise-grade orchestration layer includes built-in security, oversight, and transparency. Automated audit trails, documentation and anomaly detection minimize risk and leakage.

Also Read: Edition 3: Sharp Minds Decoding Tech’s Next Wave

Talkdesk is helping insurance companies worldwide transform their CX through the power of AI, including:

Arbella Insurance: achieved a 20% improvement in service levels and reduced average handle time (AHT) by up to 45 seconds, along with a 3% CSAT lift through unified orchestration and self-service automation.

Nassau Financial Group: realized a 4.5% reduction in transfer rates, a 90-second reduction in AHT and sustained customer loyalty, reflected in a 4.9/5.0 Trustpilot rating for service quality and reliability.

The post Talkdesk Launches AI Agents for Insurance appeared first on MartechView.

Talkdesk®, Inc. announced strategic advancements with Microsoft that deliver new ways for enterprises to improve customer experiences. Talkdesk for Microsoft Teams, a certified integration between Talkdesk and Microsoft Teams, now enables organizations to embed Talkdesk directly within Microsoft Teams. Additionally, Talkdesk Customer Experience Automation (CXA) is now available through the Microsoft Azure Marketplace.

The enhanced Talkdesk for Microsoft Teams integration brings advanced contact center capabilities directly into the Teams platform, creating a unified workspace for agents, supervisors, back-office staff, and subject matter experts across enterprises. By embedding Talkdesk Workspace within Teams, organizations can eliminate app switching, streamline collaboration, and unify employee and customer experiences. With a single interface, agents also gain advanced routing and seamless omnichannel support. In addition to presence and directory syncing, these enhancements deliver greater efficiency, faster resolution, and more consistent customer experiences.

“At Microsoft, we’re committed to empowering organizations with collaborative solutions that drive meaningful results. Embedding Talkdesk’s advanced contact center capabilities into Microsoft Teams helps customers strengthen employee productivity and deliver more seamless customer interactions within the flow of work,” said Jaime De Mora, chief technology officer for Digital Natives at Microsoft EMEA.

Furthermore, with Talkdesk CXA now available on the Azure Marketplace, enterprises have a faster path to deploy specialized artificial intelligence (AI) agents that manage both customer interactions and the underlying tasks behind them. By unifying customer data and applying continuous learning, Talkdesk CXA drives measurable improvements in efficiency, resolution times, and satisfaction. Importantly, Talkdesk CXA can be deployed on any cloud, hybrid, or on-premises contact center system without disrupting existing infrastructure.

“Portugal continues to lead in AI innovation, and this collaboration with Talkdesk reflects how Microsoft’s cloud and AI infrastructure can support digital firms in delivering more intelligent and connected customer experiences. By integrating Talkdesk’s capabilities into Microsoft Teams and making CXA available on Azure Marketplace, we’re helping organizations enhance service delivery and explore new ways to engage customers—securely, efficiently, and at scale,” said Andres Ortolá, general manager of Microsoft Portugal.

Also Read: Agile Marketers Win: Elizabeth Maxson on AI, Composability and Creativity

“The expansion of our Microsoft partnership showcases our commitment to helping enterprises deliver exceptional customer experiences inside the tools their employees use every day,” said Al Caravelli, chief revenue officer and senior vice president of strategic alliances and partnerships at Talkdesk. “Embedding Talkdesk Workspace inside Microsoft Teams and making CXA available through the Azure Marketplace means customers can accelerate innovation, streamline collaboration, and drive meaningful business outcomes.”

This announcement builds on previous collaborations between Talkdesk and Microsoft, including the partnership with SD Worx and Talkdesk’s recognition as Microsoft Digital Native of the Year in 2023. Talkdesk for Microsoft Teams is available today through the Teams AppSource marketplace. Talkdesk CXA is now available on the Microsoft Azure Marketplace.

The post Talkdesk Deepens Microsoft Partnership for CX appeared first on MartechView.