EngageLab, a global leader in AI-powered omnichannel customer engagement, has launched a new data center in Istanbul, Turkey, bolstering its global infrastructure and enhancing email delivery performance for international enterprises.

The new facility expands EngageLab’s “dual data center + multi-node” network, complementing its core centers in Istanbul and Singapore and eight global service nodes across Frankfurt, Los Angeles, Silicon Valley, Mumbai, Hong Kong, Shanghai, and others. This addition strengthens the company’s computing and storage footprint across the Eurasia–Africa corridor, ensuring low-latency and localized email delivery for global businesses.

AI-Powered Email Marketing for Smarter Engagement

EngageLab Email offers 100+ customizable templates for every stage of the customer lifecycle—from acquisition to conversion—paired with AI-driven content creation and an intuitive drag-and-drop editor. Marketers can preview emails across clients such as Gmail, Outlook, and Yahoo to ensure consistent user experiences.

The platform’s AI and data-driven capabilities enable brands to craft high-converting campaigns through automation, real-time insights, and intelligent testing, helping marketers optimize both engagement and ROI.

Enterprise-Grade Deliverability and Security

EngageLab integrates BIMI, DKIM, SPF, and DMARC protocols to secure sender reputation and improve inbox placement. Dedicated IP environments isolate performance variables, while partnerships with major anti-spam organizations ensure compliance and minimize blacklist risks.

Intelligent warm-up functions and automated A/B testing further enhance inbox placement—achieving up to 99% delivery accuracy. Marketers also benefit from real-time journey tracking, including delivery, opens, clicks, and unsubscribes, for precise performance measurement.

Strategic Hub for Eurasian Connectivity

Located at the intersection of Europe, Asia, and Africa, Turkey’s new data center positions EngageLab as a key enabler for brands expanding into the Middle East and North Africa (MENA) region. The infrastructure addresses persistent issues like high latency, inconsistent deliverability, and data localization challenges, enabling brands to:

• Meet regional data compliance standards

• Reduce email latency and improve delivery stability

• Strengthen brand reputation with localized IPs

Empowering Global Business Expansion

Serving enterprises in 220+ countries and regions, EngageLab processes hundreds of millions of emails daily, boasting an average delivery time of just three seconds. With the addition of the Turkey data center and expanded AI capabilities, EngageLab reinforces its commitment to secure, scalable, and intelligent global communication solutions.

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Bond, a leading customer intelligence-driven engagement company backed by Mountaingate Capital, has acquired Armadillo, the UK-based award-winning CRM agency known for its expertise in data-driven personalization and loyalty strategy.

The acquisition marks a major expansion of Bond’s global footprint, combining AI-powered intelligence, CRM strategy, and creative activation to help brands personalize every customer interaction and drive measurable growth. Together, the two companies now manage nearly 200 million consumer profiles and employ over 850 specialists across North America and Europe.

Uniting Data, CRM, and Loyalty for Smarter Engagement

The combined entity delivers a fully connected engagement system spanning predictive analytics, CRM and loyalty strategy, MarTech enablement, and performance measurement. By integrating Armadillo’s CRM expertise with Bond’s loyalty and intelligence platforms, the companies aim to help brands unlock precision personalization and improve customer lifetime value.

“By fusing Bond’s data science and loyalty technology with Armadillo’s CRM and personalization expertise, we’re enabling brands to personalize every moment, optimize every investment, and grow every relationship,” said Morana Bakula, CEO of Bond.

Armadillo’s Award-Winning Legacy

Founded in 1993, Armadillo has become one of the UK’s most awarded independent CRM agencies, recognized by the Data and Marketing Association (DMA) for four consecutive years. The agency’s client roster includes Disney, easyJet, Nationwide Building Society, Greene King, Cunard, and Huel — brands that rely on its MarTech-driven personalization to deliver measurable business results.

James Ray, formerly CEO of Armadillo, will assume the role of SVP, Head of CRM, Global at Bond, while Jo Penn becomes Managing Director, UK & Europe. Both will continue to oversee client relationships and lead integration efforts alongside existing leadership teams.

Expanding Bond’s Global Growth Strategy

The acquisition reinforces Bond’s position as a global leader in customer intelligence, loyalty, and behavioral science. The company’s existing client base includes Adobe, Ford, McDonald’s, Sephora, and Gap — brands that rely on its proprietary technology and analytics to deliver high-impact engagement programs.

“This acquisition substantiates our guiding principle that customer understanding drives long-lasting success,” said Bob Macdonald, Founder and Chairman of Bond. “Our depth in loyalty, coupled with Armadillo’s creative and one-to-one marketing strengths, provides clients with unparalleled engagement solutions that inspire customer action and deliver sustainable growth.”

A Unified Vision for Intelligent, Connected Growth

According to Ray, the integration is more than a merger of capabilities — it’s a cultural fit. “Marketing is at a turning point,” he said. “Together, we cut through complexity, turning brand, tech, and loyalty into one seamless engine for growth. It’s a perfect fit: same vision, same passion, all totally connected to the work and our clients.”

The move underscores Bond’s ongoing expansion strategy, further enhancing its ability to provide fully integrated, intelligence-first marketing solutions to global enterprises.

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Toronto-based digital marketing and SEO agency dNOVO Group has released a new study spotlighting the top SEO agencies in Toronto for 2025, offering an in-depth look at the firms driving digital growth in one of Canada’s most competitive online markets.

The annual report evaluates agencies on service quality, transparency, verified client satisfaction, and measurable performance outcomes, helping Canadian businesses identify reliable partners for their search marketing strategies.

dnovo Group Leads in SEO Innovation

According to the study, dnovo Group itself emerged as a top leader in Toronto’s SEO landscape. Rankings were based on a blend of quantitative and qualitative criteria, including verified reviews, client responsiveness, pricing transparency, and industry specialization.

The research team also conducted a technical SEO audit, reviewing website performance, search health metrics, and case study credibility to ensure rankings reflected real-world results, not just reputation.

The Advantage of Local SEO Expertise

The report highlights that Toronto-based agencies provide a distinct competitive edge for Canadian businesses. Local SEO firms not only understand Google’s evolving algorithms but also the cultural nuances, bilingual audiences, and regional search patterns that shape engagement across the Greater Toronto Area.

“Local context is everything,” the study notes. “The way people search in Scarborough or Etobicoke isn’t identical to Bay Street professionals or Yorkville boutiques. The best Toronto SEO agencies know how to connect brands with these unique audiences.”

AI Search Optimization Defines the Next Frontier

dnovo’s analysis also underscores the growing role of AI-driven SEO, with top-performing agencies optimizing for emerging AI search platforms such as Google SGE (Search Generative Experience), ChatGPT, and Perplexity.

This shift marks a new era in search marketing, where authenticity, user intent, and transparency are critical for visibility and growth. According to the report, agencies that integrate AI insights, automation, and content adaptability will set the standard for next-generation SEO performance in 2025 and beyond.

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Enterprise marketers love talking about AI, automation, and cutting-edge martech. Yet a new survey suggests most of that hype falls apart at the foundation: the data feeding those tools. According to fresh research from Intermedia Global (IMG), only 2% of UK marketing leaders rate their data quality as strong and flowing cleanly through their martech stack. In other words, 98% are operating with data that slows them down—or worse, derails their ambitions.

The study, which surveyed 250 C-suite executives running marketing technology budgets within mid-sized UK enterprises (£100m–£500m in revenue), exposes a deep operational gap. Despite a decade of martech expansion, data remains the weakest link.

Data Inefficiencies Are Draining Budgets—and Patience

Marketers often blame slow performance on tools, teams, or budgets. Yet IMG’s findings point to something far simpler: poor data flow. And the consequences show up everywhere.

Nearly half of respondents waste time manually pulling reports. Forty-four percent say weak data slows learning cycles and triggers repeat mistakes. Even more concerning, 42% admit they lose budget because existing tech is underused or misused. Another 40% struggle with broken targeting and wasted media spend—a costly issue in a market where every click is scrutinised.

These pain points reflect a deeper structural problem. Martech stacks have grown rapidly, but integration rarely keeps pace. When the pipes are clogged, nothing downstream works as promised.

AI’s Value Hinges on Data Readiness

IMG’s data planning lead, Emily Crisp, points out that the problem isn’t a lack of awareness. In fact, 91% of CMOs say data quality directly affects campaign performance. What’s missing is action—and the discipline required to fix foundational issues before adding new technology.

Crisp also highlights a growing disconnect: brands are pouring money into AI tools while ignoring the data requirements those tools depend on. MIT’s recent findings show that 95% of companies have yet to see ROI from generative AI pilots. The issue isn’t AI—it’s the poor-quality data feeding it.

Tools powered by machine learning amplify whatever they ingest. If the inputs are messy, the outputs will be worse. In short, AI cannot rescue bad data. It only exposes it.

The Real Path Forward: Fix the Data, Not the Stack

The martech industry has long been obsessed with adding new platforms, integrations, and “next-gen” capabilities. IMG’s research is a blunt reminder that innovation without operational discipline rarely delivers value.

Crisp puts it plainly: improving data flow is the first step toward better performance. Ignoring it creates friction at every stage of the marketing lifecycle. Before CMOs chase new AI promises, they must address the fundamentals—governance, hygiene, enrichment, and cross-platform consistency.

It may not be glamorous, but it is transformative. Strong data turns existing martech into high-performing assets. Weak data turns even the most advanced tools into expensive clutter.

For marketing teams under pressure to prove ROI, this is the wake-up call. AI will not fix the martech ecosystem. But clean, efficient data just might.

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OpenText just expanded its enterprise footprint—and its AI ambitions—by securing official certification for SAP S/4HANA Cloud Public Edition. With this move, OpenText becomes an SAP Solution Extensions partner offering a cloud-ready document management platform built to support SAP’s flagship Cloud ERP. For customers, that means deeper control, cleaner compliance, and faster digital workflows across increasingly complex environments.

It’s a strategic shift with real weight. Enterprises migrating to SAP Cloud ERP are demanding ways to connect their structured SAP data with the massive volume of unstructured content scattered across the business. Without that connection, AI initiatives stall, processes break, and decision-making suffers. OpenText wants to solve that — and do it natively inside the SAP ecosystem.

Why This Certification Matters

SAP Cloud ERP has become the operating backbone for organizations pursuing large-scale modernization. But process performance depends heavily on the ability to unify content and data. OpenText Core Content Management plugs directly into this need, offering governed, AI-ready content controls that extend SAP’s structured workflows.

The logic is simple: AI is only as good as the information feeding it. The more unified the content, the better the outcomes. With this certification, SAP customers gain a cloud-first layer of automation, transparency, and compliance designed for large, distributed enterprises.

SAP’s Darryl Gray underscored the point, calling the partnership “a catalyst for high-performance in the cloud ERP era.” His message is clear—real modernization requires content and process to move in lockstep, and the OpenText–SAP integration attempts to deliver that alignment at scale.

AI-Ready Information Starts With Unified Content

The companies argue that AI value collapses without deep access to reliable unstructured content. Emails, contracts, customer communications, recorded interactions—these assets shape context but rarely live in accessible, governed environments. OpenText wants to fix that by creating what its CMO Sandy Ono describes as a “unified view of all enterprise knowledge.”

In practice, that means surfacing content within SAP Cloud ERP to support planning, procurement, finance, supply chain, and every operational layer depending on consistent information. By removing silos, enterprises should gain cleaner insight pathways, stronger compliance controls, and fewer blind spots when deploying AI across mission-critical workflows.

What Customers Can Expect

With native integration comes several tangible upgrades:

• Automation at scale across document-heavy processes

• AI-ready content pipelines that unify structured and unstructured data

• Embedded compliance aligned with SAP Cloud ERP governance models

• Cloud-first agility that reduces integration work and operational overhead

For enterprises wrestling with fragmented content management, the offering provides something rare: a single, native path to govern information globally while preparing it for AI use cases.

The Bigger Picture

The certification signals where enterprise software is heading. ERP platforms may remain the system of record, but content platforms are quickly becoming the system of insight. As AI adoption accelerates, the pressure to unify data and content will rise, making partnerships like SAP and OpenText far more consequential than a typical product extension.

For now, OpenText’s certification gives SAP Cloud ERP customers a clearer route toward intelligent, compliant, and AI-enabled operations — without stitching together yet another integration layer.

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Crest Data just landed a distinction held by only 0.1% of AWS Partners. The company has earned the AWS Cloud Operations Competency in Monitoring and Observability, a certification that validates its deep technical expertise in helping enterprises optimize performance across AWS environments. The announcement arrives alongside the launch of Crest Data’s Migration Acceleration Service for Amazon CloudWatch, now available in the AWS Marketplace.

This combination—elite certification plus a dedicated migration engine—marks a serious push to reshape enterprise observability strategies. It also positions Crest Data as a preferred partner for organizations looking to ditch legacy monitoring tools and consolidate operations on Amazon CloudWatch.

A Rare Certification That Signals Serious Expertise

Only a fraction of AWS Partners meet the performance bar for Cloud Operations Competency. Crest Data joins that small tier with a focus on monitoring and observability, two areas that have become essential for cloud-native performance.

The certification highlights years of collaboration with AWS, backed by significant hands-on migration experience. CEO Malhar Shah says the competency is a milestone that strengthens the company’s long-running partnership with AWS. For enterprises, it signals a more reliable path to managing modern, distributed applications on AWS without adding operational burden.

Solving the Pain Points of Observability Migration

Observability platform migrations rarely go smoothly. They’re slow, expensive, and intricately tied to compliance, workflows, and existing engineering practices. Platforms overlap for months during transitions, doubling cost and complexity. Crest Data’s new service attempts to cut through this by automating most of the heavy lifting.

The company claims its migration engine automates up to 90% of dashboard and alert conversions, reducing project timelines by 60%. With over 100 migrations completed, Crest Data’s consulting teams handle the remaining nuance—tag structures, field mappings, SLO alignment, and architectural refactoring—without derailing operations. Combined, the automation and expertise make migrations at least 60% more cost-effective than traditional approaches.

Early customers appear to back the claims. AML Partners reports that Crest Data helped achieve full observability coverage across customer application stacks through Amazon CloudWatch, strengthening reliability and SLO performance.

Unlocking Advanced CloudWatch Capabilities

Organizations moving to Amazon CloudWatch through Crest Data’s service can tap into a broader suite of modern features, including:

• Advanced metrics and alarms

• Cross-account and multi-region observability

• AI-driven anomaly detection

• Enhanced database observability

These capabilities matter as enterprises scale distributed systems and build AI-ready operations. Legacy observability tools often struggle with high cardinality, multi-region complexity, and cloud-native signal volume. CloudWatch’s newer feature set, paired with Crest Data’s automation, helps close those gaps at a more palatable cost.

The Bigger Impact on Cloud Observability

The combination of AWS competency and a new migration engine positions Crest Data as a strategic player in the cloud observability market. As more organizations face budget pressure and tool sprawl, consolidating onto CloudWatch becomes increasingly attractive. Crest Data’s offering is timed for that shift, promising faster migrations with less disruption and a clearer path to unified cloud monitoring.

Enterprises betting on AWS as their primary platform now have a partner capable of delivering observability modernization without the usual pain, cost, or technical drag. And in a market where platform sprawl slows innovation, that advantage is not small.

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CallMiner just secured a notable position in the refreshed CMP Research Prism for Conversational IVR/Voicebot, earning recognition as a core performing provider. The designation reinforces CallMiner’s momentum in the fast-expanding market for AI-driven self-service, conversational voice automation, and customer experience (CX) intelligence.

The timing is strategic. The voice channel, long dependent on rigid touch-tone IVRs, is undergoing a major reboot. CMP Research notes that conversational AI, generative models, and emerging agentic capabilities are driving leaders to modernize their automated voice systems. And CallMiner sits squarely at the center of that shift.

Self-Service Demand Is Driving AI Investment

CallMiner’s own 2025 CX Landscape Report highlights the trend: 40% of senior CX and contact center leaders say AI’s biggest CX benefit is enabling customers to resolve issues independently. That aligns with rising expectations for fast, low-friction self-service—especially during periods of workforce strain and tight customer experience budgets.

CMP Research’s latest evaluation examines 20 voicebot vendors and positions CallMiner among those helping enterprises advance automation strategies while improving customer satisfaction. In a crowded field, this placement signals that CallMiner is delivering measurable value in real-world deployments.

OmniAgent Brings Voice-Optimized Automation to the Forefront

A major contributor to CallMiner’s performance is CallMiner OmniAgent, the company’s virtual agent solution built specifically for voice. The platform uses AI to automate omnichannel interactions with natural, human-like delivery. According to CallMiner, organizations using OmniAgent can reduce operational costs while improving the quality and consistency of customer engagements.

The real differentiator is its integration with CallMiner’s broader conversation intelligence platform. This pairing gives enterprises an end-to-end loop: identify which conversations to automate, deploy optimized flows, and continuously monitor automated interactions to refine accuracy and improve outcomes. It turns automation from a static deployment into a living system that learns.

CEO and founder Jeff Gallino says the companies that stand out in the automation wave will balance efficiency with customer experience. He argues CallMiner is already there, delivering “seamless, personalized automation” powered by insights extracted from real customer interactions.

A Framework Designed for CX Decision-Makers

CMP Research’s Prism is one of the few evaluation models built exclusively for customer contact and CX leaders. Updated twice a year, it reflects the latest market performance and technology advancements. For buyers navigating a crowded landscape, the Prism’s positioning helps distinguish vendors based on measurable capabilities, not marketing claims.

Nicole Kyle, Managing Director of CMP Research, says the framework exists to give decision-makers clear guidance during high-stakes technology evaluations. With AI voicebots accelerating in maturity and adoption, these assessments are becoming essential for risk-averse CX leaders planning long-term automation strategies.

The Bigger Market Signal

Recognition in the Prism suggests CallMiner is well-positioned as enterprises shift toward digital-first voice automation. Demand for conversational IVR and voicebots is rising quickly, driven by the need for efficiency, reduced wait times, and personalized self-service experiences. As AI models power more natural, accurate voice interactions, platforms like OmniAgent are becoming critical infrastructure for modern contact centers.

With AI reshaping expectations across CX, CallMiner’s growing influence indicates a broader industry pivot—one where conversation intelligence and automation aren’t just add-ons, but core pillars of customer engagement.

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PitchBook is bringing generative AI directly into the heart of private capital research. The company today announced PitchBook Navigator, a natural-language, AI-powered feature that lets users surface private market insights instantly through simple prompts inside the PitchBook Platform. Navigator will be available to subscribers in late November.

PitchBook also revealed an upcoming Model Context Protocol (MCP) integration with OpenAI, enabling subscribers to securely access PitchBook’s proprietary datasets directly within ChatGPT. Together, these launches push private market analytics into a new phase—one defined by trusted AI, faster research, and seamless cross-platform intelligence.

AI Needs Quality Data—PitchBook Claims It Has Both

“AI is only as powerful as the data and research behind it,” said Paul Jaeschke, Chief Product Officer at PitchBook. With Navigator and a growing network of LLM partnerships, the company aims to merge the speed of generative AI with the rigor of its proprietary data—long considered a gold standard in private markets.

Navigator uses natural-language queries to deliver insights across companies, deals, and market themes. It’s powered by PitchBook’s AI + HI (Artificial Intelligence + Human Insights) methodology, combining automated intelligence with human validation. The goal: responses that are fast, consistent, and anchored in verified data.

At launch, Navigator supports deal sourcing, due diligence, and market trend analysis. Over time, it will expand to cover PitchBook’s full dataset, research library, and IP portfolio. Early beta testers report faster workflows and clearer research summaries, especially for trends, summaries, and cross-market comparisons.

AI-Driven Insights, Verified at the Source

One of Navigator’s standout features is traceability. Users can review source links and underlying data references inside every response, a capability that beta testers say improves trust and simplifies verification—critical for investment teams operating under compliance constraints.

Testers also highlighted Navigator’s ability to break down queries by region, columns, or data type, offering structured, contextually intelligent outputs well beyond traditional search functions.

Bringing PitchBook Data Directly Into ChatGPT

PitchBook is also extending its enterprise AI strategy by integrating with OpenAI via MCP. Subscribers will soon be able to query PitchBook’s private market data securely inside ChatGPT, without switching tools or manually reconciling results.

The integration reflects a shared ambition: making high-quality, vetted data easily accessible in conversational AI environments. For financial professionals who increasingly rely on AI assistants for research, this could eliminate an entire layer of friction from daily workflows.

A Clear Signal of Where Private Market Intelligence Is Heading

Thomas Van Buskirk, EVP of Technology and Engineering at PitchBook, says the company’s two-decade investment in data integrity positions it well for an industry now racing toward AI adoption. PitchBook’s roadmap focuses on:

• AI-driven data collection to scale coverage with faster ingestion engines

• In-platform AI experiences including Navigator, summaries, predictive analytics, and workflow accelerators

• Strategic LLM partnerships ensuring trusted data surfaces wherever professionals work

In a market defined by speed, accuracy, and pressure to synthesize massive amounts of information, PitchBook’s moves suggest a clear direction: private market research will increasingly be conversational, integrated, and powered by verified AI.

Navigator’s launch and the OpenAI integration mark a significant step toward that future—one where data-driven decision-making moves from hours to seconds, and where trusted intelligence follows users across platforms.

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