AI may be transforming every corner of enterprise tech, but at 8x8, it’s becoming the core of customer experience. The company is reporting a sharp rise in AI adoption across its Platform for CX, driven by organizations accelerating their use of intelligent automation, omnichannel messaging, and performance tools. From real-time summarization to self-service and API-driven engagement, customers are leaning on 8x8 to reduce manual work, improve service accuracy, and deliver faster, more personalized interactions.

According to the company’s latest fiscal results, customer contracts for the 8x8 Intelligent Customer Assistant grew 59% year-over-year in Q2 FY26. Voice AI usage surged even more dramatically—up 592% year-over-year, now representing more than 81% of all AI interactions across the platform.

AI Has Shifted From Buzzword to Baseline

“AI is no longer a concept, it’s a customer expectation,” said Hunter Middleton, Chief Product Officer at 8x8. With AI embedded across every layer of the platform—from voice and messaging APIs to the contact center—the company is positioning itself as a one-stop solution for enterprises modernizing their service operations.

The data backs that up. Intelligent Customer Assistant interactions across digital, voice, and auto attendants jumped 167% year-over-year and nearly 40% quarter-over-quarter. Auto attendant AI interactions alone climbed more than 181% quarter-over-quarter. These numbers point to growing comfort with automation—not as a cost-cutting tool, but as a performance multiplier.

Messaging and Voice APIs Become CX Workhorses

Organizations are steadily increasing their use of 8x8 communication APIs to reach customers via SMS, voice, and third-party messaging apps. Interactions across messaging, voice, and video channels rose 24% year-over-year.

• SMS traffic increased nearly 20% year-over-year.

• Interactions on channels like WhatsApp, RCS, Viber, Zalo, and LINE were up 181% year-over-year and 41% quarter-over-quarter.

• Voice API interactions grew 5X year-over-year and almost 63% quarter-over-quarter.

These gains suggest enterprises are moving beyond simple automation and embracing AI-enhanced, multi-channel communication as a strategic advantage.

Cross-Industry Customer Wins Strengthen the Story

8x8’s Q2 customer momentum spans healthcare, non-profits, financial services, and supply chain sustainability—industries where reliability, compliance, and scale matter.

Highlights include:

• A major European healthcare provider deploying the 8x8 Platform for CX with Intelligent Customer Assistant.

• A U.S. healthcare network modernizing communications across operations.

• A UK non-profit adopting 8x8 Work for enhanced team collaboration.

• A U.S. regional financial services firm choosing 8x8 Conversational AI and 8x8 Voice for Microsoft Teams.

• A global supply chain sustainability leader selecting 8x8 Work and Voice for Teams.

• An international professional services company adopting 8x8 CX tools for zero-downtime deployment and improved reporting.

The diversity of wins shows the platform’s flexibility—and reinforces the expectation that AI-driven CX tools will soon become standard across industries.

New AI Features Signal Where 8x8 Is Headed

Innovation in Q2 centered on embedding AI into workflows that traditionally required heavy human input:

• Native transcription in 8x8 Work now feeds insights directly into Conversation IQ.

• Workforce Management brings forecasting, scheduling, and real-time adherence automation to the Contact Center.

• Live summarizations create real-time call summaries, reducing wrap-up time and improving CRM data quality.

• Active Calls Reporting delivers faster access to live call analytics for real-time decision-making.

These capabilities reinforce 8x8’s vision for AI-powered performance: faster, smarter operations with AI augmenting agents rather than replacing them.

A Unified Platform Built for Global Contact Centers

The 8x8 Platform for CX brings together unified communications, contact center operations, and communication APIs under one AI-driven system. By combining automation, performance intelligence, and omnichannel reach, the platform helps organizations streamline internal operations while elevating customer interactions.

AI adoption is not slowing down—if anything, it’s becoming the foundation of modern CX. With this quarter’s results, 8x8 is making a clear case for why its platform is becoming a go-to choice for enterprises that want measurable improvements, not just incremental upgrades.

Get in touch with our MarTech Experts.

Daydream, the open-source community hub for real-time AI video and world models, just took a major step toward unifying one of the most fragmented corners of AI. The company announced two significant releases: Daydream Scope, a development environment built for real-time AI workflows, and full SDXL support inside the Daydream API and Playground. Together, they push Daydream closer to becoming the open backbone of real-time video generation—a space that has quickly become essential to creative technologists, virtual production teams, and developers racing toward fully interactive AI systems.

Scope Sets the Foundation for Real-Time AI Workflows

Daydream Scope is a local, open-source toolkit designed for anyone building or experimenting with real-time video and world-model pipelines. It gives developers modular interfaces to plug in models for inference, control, and remixing—offering the flexibility needed to explore emerging real-time techniques.

Eric Tang, co-founder of Livepeer, the parent company behind Daydream, framed Scope as a foundational shift. “It gives creative technologists and builders an extensible workspace to experiment with real-time AI pipelines,” he said. Whether users are testing generative video models, constructing virtual production systems, or conducting academic research, Scope is designed as a shared sandbox where innovation can spread quickly.

Scope is still in community alpha, but it’s already delivering support for models such as LongLive, StreamDiffusionV2, and Krea Realtime 14B. New models are being added at a steady pace, underscoring the momentum behind open-source real-time video tooling.

SDXL Unlocks High-Fidelity, Low-Latency Video Generation

Daydream’s SDXL release brings a substantial upgrade in quality and control. Built on StreamDiffusion’s open architecture, SDXL merges multiple research threads into a production-ready stack. The result is high-fidelity, low-latency video generation that creators can tune and manipulate in real time.

Key capabilities include:

• IPAdapter Style Control
  Standard mode enables dynamic artistic style transfer, while FaceID mode maintains character consistency across frames.

• Multi-ControlNet Precision
  Support for HED, Depth, Pose, Tile, and Canny ControlNets delivers spatial and temporal accuracy that gives creators unmatched control.

• TensorRT Acceleration
  NVIDIA-optimized inference boosts playback to 15–25 FPS, even with complex model combinations.

For users who prefer SD1.5, Daydream hasn’t left them behind. The company paired SD1.5 with accelerated IPAdapters to offer high-framerate style transfer and improved creative consistency.

Developers Are Already Plugging In

The open ecosystem approach is paying off early. Developers like DotSimulate—the creator behind StreamDiffusionTD, a popular TouchDesigner tool—are already folding Daydream’s SDXL support into new applications. Others are experimenting with the Daydream API or self-hosting the open-source StreamDiffusion fork to build customized SDXL-based systems.

These early integrations reinforce Daydream’s vision: a real-time AI video stack that connects models, creators, and infrastructure in one coherent ecosystem.

As real-time video generation accelerates and world models inch closer to mainstream adoption, Daydream is establishing itself as one of the rare open platforms offering both speed and transparency. With Scope and SDXL now live, the company is setting the stage for the next wave of real-time AI creativity.

Get in touch with our MarTech Experts.

Inception, the startup pushing diffusion large language models into the mainstream, has raised $50 million to scale its alternative to today’s slow, costly autoregressive systems. The round—led by Menlo Ventures with support from NVIDIA’s NVentures, Microsoft’s M12, Snowflake Ventures, Databricks Investment, Mayfield, and Innovation Endeavors—marks one of the strongest signals yet that the industry is ready for a fundamental shift in how LLMs generate text.

Traditional LLMs still rely on autoregression, forcing models to generate words sequentially. That one-token-at-a-time choke point limits responsiveness, drives up compute costs, and holds back real-time AI experiences. As enterprises push for more interactive applications, latency becomes a dealbreaker.

Diffusion LLMs: A Faster Path Forward

Inception claims its diffusion-based architecture solves that bottleneck. Instead of generating text linearly, the company’s models produce answers in parallel—using similar diffusion approaches behind systems like DALL·E, Midjourney, and Sora.

The result is speed. A lot of it.

Mercury, Inception’s flagship and the only commercially available diffusion LLM, delivers responses 5–10x faster than optimized models from OpenAI, Anthropic, or Google. It hits that speed while matching accuracy, making it a compelling option for latency-sensitive workloads such as interactive voice agents, live coding environments, and dynamic user interfaces.

Speed isn’t the only advantage. Parallel generation reduces GPU usage, allowing companies to run larger models without added cost. Organizations can also serve more users on the same hardware, which is becoming crucial as AI adoption surges.

Tim Tully, Partner at Menlo Ventures, believes the technology is enterprise-ready. “dLLMs aren’t just a research breakthrough; they’re a foundation for scalable, high-performance language models that enterprises can deploy today,” he said. Backing from venture arms of NVIDIA, Microsoft, Snowflake, and Databricks reinforces the strategic importance of faster inference in an increasingly data-hungry AI ecosystem.

Fixing the Real Bottleneck: Inference, Not Training

Inception CEO Stefano Ermon argues that inference—not training—is now the barrier holding back enterprise-scale AI. As more organizations deploy LLMs across workflows, the cost of running models grows dramatically. Inefficient inference drives that cost.

“We believe diffusion is the path forward for making frontier model performance practical at scale,” Ermon said. His team includes researchers from Stanford, UCLA, and Cornell, many of whom helped develop diffusion, flash attention, decision transformers, and direct preference optimization.

That expertise is powering Inception’s push beyond speed improvements. Diffusion models offer additional benefits, including:

• Built-in error correction that reduces hallucinations

• Unified multimodal reasoning across language, images, and code

• Structured output control for function calling and data-generation tasks

These capabilities unlock new product directions across voice, coding, and advanced enterprise automation.

Funding Fuels Expansion and Real-Time R&D

The $50 million infusion will accelerate product development and expand research and engineering teams. Inception plans to deepen its work on real-time diffusion systems that span text, voice, and coding—areas where latency constraints have limited traditional LLM deployment.

The company already offers its models through the Inception API, Amazon Bedrock, OpenRouter, and Poe. Early customers are experimenting with real-time voice agents, natural language interfaces for web environments, and high-speed code generation. Because dLLMs function as drop-in replacements for autoregressive models, developers can test them without rearchitecting their systems.

A New Phase of the LLM Race

As enterprises demand faster, cheaper, and more interactive AI, diffusion LLMs could reshape what’s possible. Autoregressive systems may still dominate today, but diffusion is emerging as the challenger technology with real commercial traction.

With deep academic roots and major strategic backing, Inception is positioning itself as the company that brings this next-generation architecture into the enterprise mainstream.

If the speed claims hold up at scale, the LLM landscape may be entering its first true architectural shift since the transformer.

Get in touch with our MarTech Experts.

MarkeTeam.ai and NorthBrix have joined forces to launch CyBrixTeam AI, a market-tailored agentic marketing platform designed to give African businesses enterprise-level marketing capabilities at a fraction of traditional costs. Powered by MarkeTeam.ai’s autonomous marketing technology and operated by NorthBrix, the platform is now live in Nigeria, with expansion already planned across Africa.

This collaboration aims to tackle a persistent barrier in the region: the shortage of accessible, skilled marketing talent. As digital competition intensifies, businesses across Africa are seeking tools that help them execute campaigns faster, smarter, and with measurable impact. CyBrixTeam AI positions itself as that missing bridge.

Closing the Marketing Execution Gap

NorthBrix CEO Branka Mracajac believes the platform has the potential to shift how organizations operate. She noted that African businesses often struggle with limited resources and high execution costs, creating gaps between strategy and performance. According to her, CyBrixTeam AI offers a practical answer—reducing operational overhead while enhancing marketing sophistication.

Mracajac emphasized the platform’s transformative value: “CyBrixTeam AI empowers marketing teams and superpowers businesses. It brings enterprise-grade capabilities to regions where they were previously out of reach—faster cycles, lower cost, and measurable outcomes.”

Her framing reflects a larger trend in emerging markets: organizations want intelligent automation, but they need systems adapted to local realities, infrastructure, and workforce conditions.

A Strategic Partnership Built for Scale

For MarkeTeam.ai, partnering with NorthBrix creates a channel for delivering its autonomous marketing stack into one of the world’s fastest-growing digital landscapes. CEO Naama Manova-Twito highlighted the fit between the companies. NorthBrix’s knowledge of African business needs and its enterprise relationships enable highly customized deployments that go beyond simply dropping in new software.

“We’re excited to partner with NorthBrix in bringing our autonomous marketing technology to these dynamic markets,” she said. The partnership gives African clients access to refined AI workflows designed specifically to accelerate results while aligning with established channels and internal teams.

Inside CyBrixTeam AI: Africa’s First Agentic Marketing Layer

CyBrixTeam AI is built on MarkeTeam.ai’s proprietary Integrated Marketing Environment (IME)—the first agentic marketing platform that blends purpose-built marketing models with a team of autonomous AI agents. Unlike traditional automation tools, IME uses specialized agents capable of completing multi-step marketing tasks: analyzing data, building strategies, optimizing campaigns, and coordinating execution across channels.

Through NorthBrix, African businesses gain access to this agentic workforce on demand. The system adapts to each organization’s existing tech stack, allowing companies to integrate AI-driven processes without overhauling their infrastructure.

Key capabilities include:

• Autonomous campaign creation and optimization

• Market-specific strategy generation

• Cross-channel planning and execution

• Real-time performance measurement

• Custom workflows tailored to local industries and teams

These features create a marketing engine that businesses can scale quickly, even when internal expertise is limited.

A New Competitive Chapter for African Businesses

CyBrixTeam AI arrives at a time when digital adoption is accelerating across the continent. Companies are moving online faster than their operational teams can keep up, creating a growing need for automation that is intelligent, adaptive, and affordable.

By combining MarkeTeam.ai’s agentic marketing technology with NorthBrix’s market insight, the platform delivers a model designed to scale through real-world constraints. Its rollout in Nigeria sets the foundation for broader adoption across Africa, giving regional businesses access to tools typically reserved for global enterprises.

As competition intensifies and customer expectations rise, CyBrixTeam AI could become a defining tool for organizations seeking to grow both locally and globally without the traditional cost burden of advanced marketing operations.

Get in touch with our MarTech Experts.

BoomID, known for its biometric-driven fraud and risk management technology, has announced a new alliance with Dun & Bradstreet (D&B), the global leader in business decisioning data. The collaboration brings authoritative business insights directly into the BoomID platform, strengthening its identity authorization capabilities and expanding its ability to deliver deeper, more reliable risk assessments.

The partnership arrives at a moment when enterprises face escalating identity threats, rising vendor risk, and increasing compliance pressure. By merging biometric identity signals with D&B’s business intelligence, BoomID is positioning itself as a more comprehensive layer of trust—one that blends physical identity verification with industry-leading business data.

A Stronger Identity Authorization Framework

At the core of BoomID’s platform are proprietary risk engines that aggregate data from multiple sources to provide enhanced identity scoring. With D&B’s integration, those engines gain access to a vast network of verified business records, financial insights, and operational indicators. The combined data model allows organizations to perform more accurate, consistent checks across third parties, vendors, workforces, and even physical visitors.

BoomID frames this as an expansion of its “Always Know Your Identity” approach—a model built for environments where real-time authorization and continuous trust verification matter. Rather than treating identity as a one-time check, BoomID uses biometrics and dynamic risk scoring to determine who should access what, when, and under what level of scrutiny.

Closing Gaps in Risk, Compliance, and Fraud Prevention

CEO Ben Massin called the alliance “a significant step forward,” noting that the integration provides clients with a more powerful toolset for fraud prevention, compliance alignment, and secure access management. Organizations that rely on BoomID will now gain an added layer of intelligence, helping them assess operational risk with sharper clarity.

The blend of biometric authentication and business data also addresses a growing blind spot: identity spoofing and synthetic entities linked to fraudulent corporate structures. D&B’s authoritative data provides essential context, giving BoomID users a clearer view of who they are dealing with at every interaction.

Building Next-Gen Trust for Modern Enterprises

BoomID’s identity-centric approach moves beyond traditional authentication systems that rely solely on credentials or surface-level checks. Instead, the platform builds a real-time trust profile by merging biometric verification, behavioral signals, and enriched business data.

With the D&B partnership, enterprises can:

• Verify identities across vendors, supply chains, and workforce groups

• Detect anomalies tied to fraudulent or high-risk entities

• Strengthen compliance with regulated access policies

• Reduce onboarding risk with higher-confidence identity scoring

Together, BoomID and D&B offer a combined risk lens that aligns with how modern organizations operate—across distributed teams, hybrid infrastructures, and increasingly complex digital ecosystems.

A Strategic Move in a Shifting Fraud Landscape

Identity fraud continues to evolve, and organizations are demanding sharper, more adaptive systems. BoomID’s alliance with D&B deepens its competitive edge in the biometric identity market by pairing precision biometrics with the authoritative data backbone enterprises already trust.

By integrating risk intelligence directly into identity workflows, BoomID is laying groundwork for a more secure, transparent, and resilient trust ecosystem—one designed for real-world threats rather than legacy access models.

Get in touch with our MarTech Experts.

Pulumi is turning one of cloud governance’s biggest pain points—remediation—into an automated workflow. The infrastructure-as-code platform has introduced Pulumi Neo, an AI-powered system that identifies and fixes policy violations across multi-cloud environments. The release adds automated remediation, executive dashboards, and org-wide enforcement to Pulumi’s policy suite, now available across Team, Enterprise, and Business Critical editions.

For years, compliance and governance tools have highlighted risks across cloud estates but rarely fixed them. Platform teams routinely face thousands of violations that require painstaking manual work. In highly regulated environments, those backlogs can balloon past 100,000 issues. Pulumi is taking aim at that remediation gap with a system designed to handle scale, context, and the surrounding approval workflows.

Governance Tools Catch Violations. Neo Fixes Them.

Most policy-as-code frameworks stop non-compliant deployments but don’t touch what’s already running in the environment. Neo works differently. It analyzes misconfigurations in context, generates precise infrastructure-as-code fixes, and applies them automatically—or sends them through a configurable approval pipeline for human review.

Joe Duffy, Pulumi’s CEO and Co-founder, summed up the need: “Detection is necessary but not sufficient. Platform teams tell us they can’t keep pace with the volume of violations their tools identify. Neo closes that gap by generating and applying fixes when teams choose.”

Neo’s design acknowledges a reality facing every large cloud operation: visibility without action is no longer enough. Enterprises want faster compliance cycles, reduced security exposure, and a way to tame sprawling cloud footprints without adding headcount.

Audit-Ready Governance With Policy as Code

Customers like Spear AI are already seeing measurable impact. CEO Michael Hunter shared that auditors now prefer Pulumi’s policy packs over static documentation because code-based controls are easier to evaluate. By automating the review process, the company expects to shrink its Authority to Operate timeline from 18 months to three.

Pulumi’s policy engine supports major cloud providers and works even when organizations haven’t migrated infrastructure to Pulumi IaC. The platform includes pre-built frameworks for CIS, NIST, PCI DSS, HITRUST, ISO 27001, and SOC 2. Teams can enforce policies at deployment time, scan existing resources for misconfigurations, and feed violations into Neo to handle cleanup.

IDC: The Real Problem Isn’t Detection—It’s Capacity

Jim Mercer of IDC highlighted a growing industry-wide challenge: visibility is no longer the bottleneck. Remediation is. Teams are drowning in violation backlogs faster than they can process them. AI-powered remediation tied to policy-as-code, he said, represents a chance to push governance beyond reporting and into action.

This shift mirrors broader enterprise trends. Organizations are asking AI to automate operational drudgery, reduce risk, and clear bottlenecks that slow development. Infrastructure governance is emerging as one of the most urgent—and impactful—targets.

A Step Toward Autonomous Cloud Governance

With Neo, Pulumi is nudging the industry toward automated, self-healing cloud environments. Instead of relying on engineers to track and fix endless violations, organizations gain a system that continuously enforces compliance boundaries while maintaining human oversight where needed.

For platform and security teams stretched thin across multi-cloud estates, Neo signals a future in which governance becomes proactive, automated, and materially faster—turning compliance from a roadblock into an operational advantage.

Get in touch with our MarTech Experts.

fal, the fast-growing generative media platform used by developers worldwide, has made its first acquisition: Remade, a Y Combinator–backed startup building AI-native tools for creative and design teams. The move strengthens fal’s position as one of the leading infrastructure providers for image, video, and audio generation, while adding a polished creative workspace built by a team known for rapid innovation.

Founded in 2021 by engineers Burkay Gur and Gorkem Yurtseven, fal gives developers API-level access to more than 600 image, video, and audio models through serverless GPU infrastructure. The company is one of only 33 U.S. AI firms to raise more than $100 million in 2025, with enterprise customers like Adobe, Canva, Perplexity, and Shopify relying on fal to power large-scale generative workloads.

A Strategic Fit for Generative Media’s Next Phase

Remade caught fal’s attention for good reason. The startup, founded in 2024 by four Cambridge University computer science graduates—Blendi Bylygbashi, Christos Antonopoulos, Alex Matthews, and Rehan Sheikh—built an AI-native workspace designed for design and marketing teams. The product unified access to modern image and video generation models, simplifying workflows that often require juggling multiple tools.

Remade’s technology proved popular fast. Its open-source Wan 2.1 Video LoRAs have been downloaded more than 250,000 times, becoming one of fal’s most frequently used endpoints. For a young team shipping at an unusual pace, the acquisition reflects both capability and timing.

Antonopoulos, now joining fal, said Remade’s team recognized early how crucial fal’s infrastructure was to the generative media ecosystem. “When we started talking with Burkay, it was incredible to hear his vision for the future of generative media and how we could accelerate it,” he said.

Talent and Technology That Bolster fal’s Vision

fal CEO Burkay Gur highlighted the talent behind Remade as a major factor. “The pace at which these four founders shipped high-quality code was impressive,” he said. “They have an exceptional understanding of how fal helps developers and they stay ahead in the fast-paced generative media space. We love their hustle and are glad to have them on the team.”

The acquisition is expected to help fal bridge the gap between developer infrastructure and creative tooling. While fal has long focused on providing robust model access and serverless GPU performance, Remade adds front-end workflows more aligned with the needs of marketing, design, and creative teams.

Massive Scale and Momentum in Generative Media

fal’s momentum continues to build. In February, the company surpassed 100 million generative media requests per day while maintaining 99.99% API uptime. It partners with top generative model developers including Black Forest Labs, Google, Alibaba, ByteDance, and Hailuo.

To support developers evaluating rapid advancements in generative models, fal recently released a developer sandbox environment. The sandbox lets users test multiple models against identical prompts, helping them benchmark performance, evaluate quality, and decide which models to bring into production.

Antonopoulos said the team is eager to iterate further: “The fal sandbox is something we’ve been waiting for as developers ourselves. We’ll continue incorporating feedback from our dev community to make it better to build with any model on fal.”

A Consolidation Moment in Generative Media

The acquisition underscores a broader trend: generative media platforms are moving toward unified ecosystems that support both deep infrastructure and accessible creative tools. As developers and creative teams converge around real-time AI workflows, companies like fal are positioning themselves at the center of that shift.

By integrating Remade’s workspace with its scalable API infrastructure, fal is building toward a future where developers can test, deploy, and refine generative systems while creative teams work in interfaces tailored to their needs—all powered by the same underlying platform.

Get in touch with our MarTech Experts.

Alchemer has reached a major milestone in its push to make customer feedback more actionable and integrated. The company announced that Alchemer Connect has surpassed 10,000 unique automated workflows, powering millions of customer interactions across platforms such as Salesforce, HubSpot, Zendesk, Workday, Braze, Shopify, and WooCommerce.

More than 50% of Alchemer’s business platform customers rely on Connect integrations—strong validation that organizations want feedback systems tied directly to the tools their teams already use. As companies grow frustrated with feedback that lives in isolation, Alchemer is positioning itself as the platform that turns insight into immediate action.

This milestone underscores a shift across customer experience, operations, and HR teams: collecting feedback is no longer enough. Acting on it—instantly and at scale—is the new standard.

Seven-Day Onboarding Sets an Industry Benchmark

One standout metric from Alchemer’s announcement: the company now leads the market with a seven-day average onboarding period. In a landscape where many feedback platforms require weeks or months of implementation, Alchemer Connect allows organizations to deploy automated workflows in days—without tapping scarce IT resources.

The speed and flexibility of Connect are helping teams address high-value use cases fast, from customer recovery to employee engagement. The platform’s adaptability also enables teams to experiment, iterate, and operationalize “what if” scenarios without heavy technical support.

“Organizations no longer want feedback that sits in isolation; they want insights that drive action instantly,” said Ryan Tamminga, Senior Vice President of Customer Success & Product at Alchemer. He emphasized that integrating insights directly into business systems is where Alchemer excels, empowering teams across marketing, operations, HR, and customer experience.

Why Organizations Are Turning to Alchemer

Alchemer Connect’s traction is tied to both measurable value and ease of adoption.
Customer data from the company highlights:

• 92% of customers say ROI met or exceeded expectations

• 80% cite fast, seamless implementation as a top benefit

• Responsive support teams help organizations maximize their investment quickly

These insights reveal a clear pattern: companies want CX tools that integrate, automate, and produce results without long delays or technical barriers.

Real-World Impact Across Industries

Organizations across sectors—including retail, healthcare, government, and education—are using Alchemer Connect to operationalize feedback and improve outcomes.

Ryder System, Inc.

Ryder deployed Alchemer Connect across multiple business units, using automated workflows to enhance both customer and employee experience programs. The integrations have helped the company improve operations, gather better insights, and scale quickly across diverse use cases.

City of Salem, Oregon

Salem uses Alchemer to support multi-department engagement efforts, including public trust initiatives and municipal operations. Automated workflows streamline collaboration and surface insights that help the city improve community outcomes efficiently.

These examples highlight a broader trend: organizations want a feedback engine that adapts to their processes—not the other way around.

Feedback Operationalization Becomes a Competitive Advantage

Alchemer’s recent growth points to a larger shift in how organizations view customer and employee feedback. Instead of treating feedback collection as a standalone function, companies are increasingly embedding it into the core of their workflows.

By enabling real-time service recovery, personalized customer journeys, and employee-driven insights, Alchemer Connect is helping teams respond faster and create more consistent experiences. The ability to implement and operationalize feedback rapidly also allows organizations to react to market changes with agility.

The company’s momentum signals a new era of integrated customer experience—where speed, automation, and connected workflows increasingly determine who captures value first.

Get in touch with our MarTech Experts.