In a move set to reshape tax operations for large enterprises, Deloitte Tax LLP has expanded its alliance with Databricks to modernize data management services for tax departments. The partnership aims to create a single source of truth for tax-related information, streamlining operations while supporting AI-driven insights.

Modernizing data infrastructure is critical as tax teams increasingly adopt Generative AI and advanced analytics. A unified, well-governed tax data environment enables departments to reduce integration costs, improve regulatory reporting, respond faster to audit requests, and develop forward-looking strategies.

What’s New: Unified Data, Automation, and AI

The expanded alliance focuses on three major areas:

• Unified Tax Data Architecture: Consolidates information from multiple sources to improve consistency, reliability, and operational efficiency.

• Automated Digital Tax Documentation: Intelligent automation reduces manual work and strengthens audit readiness while boosting precision in filings and records.

• Advanced Solutions for Global Tax Complexity: Analytics and modeling tools help tackle intricate regulations, including Pillar Two and other international requirements, allowing tax teams to proactively manage compliance.

By leveraging the Databricks Data Intelligence Platform, Deloitte Tax can enhance visibility across enterprise-wide tax data, providing a scalable and secure foundation for deploying AI models in reporting and interactive dashboards.

Industry Implications

As tax departments face increasing pressure to operate efficiently while staying compliant across multiple jurisdictions, this alliance positions Deloitte Tax at the forefront of data-driven tax transformation. The integration of cloud-based solutions and AI-powered workflows could significantly reduce manual processes and accelerate decision-making, while offering a template for other professional services firms navigating digital transformation.

“Modernizing tax operations is crucial for meeting clients’ dynamic needs,” said Carin Giuliante, CEO of Deloitte Tax. “By harnessing Databricks’ cutting-edge platform, we can deliver scalable, efficient, and secure solutions that empower strategic decision-making.”

Bavesh Patel, SVP at Databricks, added, “This collaboration enhances our solutions and opens new avenues for innovation, positioning tax departments to stay ahead in an increasingly complex, data-driven world.”

With this expanded alliance, Deloitte Tax and Databricks are not just streamlining current operations—they’re laying the groundwork for AI-enabled, agile tax functions that can adapt to evolving regulations and enterprise demands.

Get in touch with our MarTech Experts.

">

Product teams often struggle to keep up with the pace of modern software development. Feedback is scattered across support tickets, surveys, and calls, while manual analysis creates bottlenecks that slow decision-making. Dovetail aims to fix that with the launch of its AI-native customer intelligence platform, designed to turn customer feedback into actionable insights and real-world prototypes—fast.

The platform closes the gap between customer signals and product execution. AI structures feedback into requirements, surfaces insights, and delivers them directly into prototyping and coding environments. The result: product momentum stays constant, and teams build features that customers actually need.

Turning Feedback into Action

Dovetail’s platform operates as a continuous four-stage cycle:

1. Assemble: Centralizes every customer voice—sales calls, support tickets, surveys, app reviews, usability tests, and more.

2. Analyze: Uses AI to classify feedback, build dashboards, compare segments, and track sentiment shifts.

3. Uncover: AI-powered Chat surfaces insights, generates PRDs, research reports, and Voice of Customer updates.

4. Act: Closes the loop with Linear tickets, Slack alerts, automated reports, and Alloy prototypes.

As part of its launch, Dovetail announced a partnership with Alloy, enabling captured feedback to instantly become live prototypes. Coding platform integrations are on the way, further bridging the gap from insight to execution.

Key Features for Fall 2025

• AI Contextual Chat: Drill into data with scoped, relevant answers.

• AI Docs: Generate PRDs, VoC reports, and summaries with citations.

• AI Agents: Intelligent operators that act on Dovetail data autonomously.

• Dashboards and Segments: Visualize sentiment and slice intelligence by ARR, plan, or region.

• Integrations: Enrich accounts with Salesforce, sync calls from Gong, import Outset reports, and link Linear issues directly from Dovetail.

Scaling Intelligence Across Teams

By unifying signals from product, design, ops, sales, marketing, and customer success, Dovetail ensures teams operate from a single source of truth. AI accelerates analysis, making insights immediately accessible to the people who need them.

“Building great products has never been the job of one team,” said Benjamin Humphrey, CEO and co-founder of Dovetail. “Sales, success, product, and design all bring critical signals, but too often those signals are fragmented or lost. With the Dovetail customer intelligence platform, we bring every voice together, analyze them with AI, and make them accessible across the organization.”

With this platform, Dovetail positions itself as the operating system for customer-led product development, enabling faster, smarter, and more coordinated decision-making across modern product organizations.

Get in touch with our MarTech Experts.

Utilities are facing a looming challenge: by 2030, energy demand is projected to rise 25%, with peak electricity demand climbing 14%. To help utilities meet these pressures, ICF (NASDAQ:ICFI) has unveiled the next generation of Sightline®, its industry-leading platform for utility program management.

The upgraded platform brings AI-powered analytics and insights that give utilities a 360-degree view of customer programs. Sightline can now pinpoint high-demand periods, predict grid stress, and optimize energy efficiency initiatives to reduce costs while enhancing customer engagement.

Smarter, Faster Utility Program Management

Sightline’s enhancements include centralized business intelligence dashboards and analytics that enable faster program design and real-time management. Utilities can see how customer energy usage impacts the grid, allowing them to make timely, data-driven decisions that benefit both operations and customers.

“Utilities must be equipped to make data-driven decisions with greater precision and agility when navigating a much more complex and dynamic grid,” said Kyle Wiggins, ICF senior VP and utility programs lead. “Our latest upgrade to Sightline enhances data integration, workflow automation, analytics, regulatory reporting, and customer engagement.”

The upgrade also comes on the heels of ICF’s AEG acquisition, strengthening the company’s capabilities in demand-side management and customer program support.

Meeting the Challenges of a Changing Energy Landscape

As energy consumption rises and distributed energy resources proliferate, utilities need flexible, modular solutions. Sightline’s architecture allows utilities to simplify operations, optimize incentives, forecast adoption trends, and measure the impact of demand-side management programs—even at the individual customer level.

Already deployed by over 90 utilities and government entities across the U.S., Sightline helps clients simulate program value, anticipate customer behavior, and plan interventions that enhance grid reliability and reduce the need for costly infrastructure upgrades.

With this next-gen release, ICF reinforces its position as a leading energy consultancy, providing end-to-end solutions for utilities, energy developers, and government agencies—from strategy and planning to implementation and analysis.

Get in touch with our MarTech Experts.

Marketers constantly juggle the risk of over-communicating with customers while striving to maximize engagement. Hightouch, a leading data and AI platform for marketing and personalization, is addressing this challenge with Smart Suppression, a new feature in its AI Decisioning suite.

Traditional suppression rules—like static frequency caps—treat all messages equally, leaving marketers to choose between lost conversions or damaged relationships. Smart Suppression introduces a smarter, data-driven approach.

How Smart Suppression Works

The feature taps into customer data from warehouses, including purchase history, engagement patterns, and behavioral signals, to predict which messages will deliver incremental lift and which could risk unsubscribes or harm brand equity. Marketers can set suppression thresholds through the AI Decisioning interface, giving them direct control while automatically filtering out risky messages.

“Decisioning agents are greedy. They're designed to maximize outcomes, and if you give them permission to send five times a week, they'll send five times a week,” said Rishabh Anand, Product Lead for AI Decisioning at Hightouch. “Smart Suppression ensures they focus that volume on messages that actually drive impact, not just fill quotas.”

Unlike black-box optimization tools, Smart Suppression balances automation with marketer oversight, ensuring that AI-driven campaigns enhance customer relationships without unintentionally driving unsubscribes or damaging sender reputation.

Implications for Lifecycle Marketing

By predicting the impact of each message, Smart Suppression helps marketing teams maximize engagement while protecting brand equity, a critical differentiator in crowded digital channels. As AI-driven personalization becomes the norm, tools like this offer a way to scale outreach intelligently without sacrificing customer trust.

With this launch, Hightouch reinforces its position as a platform that combines data-driven decisioning with marketer control, allowing organizations to send smarter, safer, and more effective communications.

Get in touch with our MarTech Experts.

The financial industry’s obsession with precision meets its latest ally: AllocateRite, the world’s first deterministic AI-powered wealth management platform, has rolled out a Marketing Compliance Tool designed to tackle one of finance’s most persistent pain points—marketing oversight in a regulated world.

In an era where a misplaced logo or an overlooked client name in a pitch deck can trigger data privacy penalties, AllocateRite’s solution promises to make compliance less of a bottleneck and more of a built-in safeguard. The new platform reviews content before publication, flags potential regulatory breaches, and suggests fixes in real time—all without slowing down marketing cycles.

“Marketing compliance shouldn’t be a blind spot—or a brake pedal,” said Abbas Shah, Co-Founder and Chief Algorithm Officer at AllocateRite. “We’re giving firms a single, auditable system of record for compliant marketing at scale. This release is a new use case for our deterministic AI platform—the same financial-grade infrastructure that already powers mission-critical enterprise workflows.”

A Compliance Engine Built for Speed and Scrutiny

AllocateRite’s Marketing Compliance Tool scans over twenty content formats—from videos and social posts to PDFs and podcasts—against firm rules and regulatory guidelines. The system delivers explainable, consistent results while routing content through structured review workflows. Every action is logged, from who made edits to when approvals were granted, creating an audit-ready record regulators can trace from draft to publication.

The impact is measurable: firms can now move from first draft to final approval in days instead of weeks, reduce regulatory exposure through built-in AI checks, and lower compliance costs by automating repetitive review tasks.

Context: A $40 Billion Marketing Problem

The financial services sector spends more than $40 billion annually on marketing—and devotes thousands of compliance hours to manually vetting content. Most firms still rely on outdated systems ill-equipped for today’s multi-channel, real-time marketing environments.

AllocateRite’s solution steps into this gap with a deterministic AI model—a key distinction from probabilistic systems that can produce unpredictable results. Deterministic AI ensures every decision is traceable, auditable, and explainable—an essential feature for risk-sensitive industries like wealth management and asset advisory.

Why It Matters

In a post-GDPR, SEC-scrutinized landscape, marketing compliance has evolved from a back-office formality to a front-line defense against regulatory fallout. AllocateRite’s launch signals a broader shift: AI is no longer just a trading or analytics tool—it’s becoming the new backbone of marketing governance in financial services.

Get in touch with our MarTech Experts.

Bluefish, an AI marketing platform for the Fortune 500, has added a major name to its leadership circle: Peter Naylor, the advertising executive who’s shaped digital media from the early streaming era to the AI revolution.

Naylor, whose résumé includes senior roles at Netflix, Snap, Hulu, and NBCUniversal, joins Bluefish as a strategic advisor, bringing deep expertise in building ad ecosystems and guiding global brands through technology-driven transformation. His appointment underscores Bluefish’s growing ambition—to help CMOs and enterprise marketers build scalable, AI-powered marketing systems in a rapidly changing digital landscape.

From Streaming Pioneer to AI Marketing Strategist

Naylor’s career reads like a timeline of modern advertising. At NBCUniversal, he helped define digital video ad formats that would later become industry standards. At Hulu, he helped prove that streaming could sustain premium ad experiences. And at Netflix, he led the company’s global ad sales during its crucial pivot into ad-supported streaming—arguably one of the most closely watched experiments in digital media.

Now, Naylor turns his attention to AI as marketing’s next disruptive frontier.

“Consumer journeys are rapidly migrating from traditional search paradigms into a new landscape of answer engines and AI applications,” said Naylor. “What excites me about Bluefish is the urgency and scale of the problem they’re tackling. This is a transformative moment for marketers.”

Bluefish’s Bet on AI-Driven Marketing Systems

For Alex Sherman, CEO of Bluefish, Naylor’s arrival is both strategic and symbolic. “AI is disintermediating large brands from the customer,” Sherman said. “Peter’s experience leading large-scale marketing deployments will help us partner more deeply with global enterprises as we build the marketing systems of the future.”

Bluefish, fresh off a Series A funding round, is positioning itself at the center of an industry in flux. As AI tools redefine how consumers discover brands—shifting from keyword-based search to conversational interfaces and “answer engines”—the company aims to give marketers visibility and control in this new environment.

The Industry Signal

The addition of a veteran like Naylor signals confidence in Bluefish’s trajectory—and highlights a broader movement among enterprise marketers to integrate AI governance, creative automation, and media optimization under unified platforms.

For Naylor, it’s another chance to shape an inflection point in marketing history—this time not as a media seller, but as a builder of the systems that define how AI connects brands and consumers.

Get in touch with our MarTech Experts.

As ransomware attacks evolve from disruptive to downright destructive, Recovery Point Systems is taking no chances. The Maryland-based cyber resiliency and business continuity provider has upgraded its Ransomware Recovery as a Service (RRaaS) offering with a new AI-powered feature: Backup Validation—a proactive safeguard that verifies the health and integrity of backup images before recovery even begins.

The move targets one of cybersecurity’s most underappreciated weak points: compromised backups. According to Veeam’s 2023 Ransomware Trends Report, 93% of ransomware attacks now target backup infrastructure directly, and three out of four organizations report failed recoveries after a cyberattack. Recovery Point’s new validation layer aims to close that gap.

“Backups alone don’t guarantee resilience,” said Brett Moss, President of Recovery Point Systems. “What differentiates us is orchestrated, validated recovery. Our Backup Validation assures clients their backups are intact, clean, and fully restorable—even against dormant malware that slips past frontline defenses.”

Clean, Tested, and Ready to Recover

Traditional backup tools confirm only that data was saved—not that it’s safe or usable. Recovery Point’s Backup Validation performs full system-level testing within an isolated cleanroom environment at its data centers. Here, AI algorithms automatically power up backups, perform malware scans, assess recoverability, and assign resilience scores.

That means organizations can detect infections or corruption before a crisis, satisfying both regulatory mandates and cyber insurance requirements with compliance-ready documentation.

The service integrates seamlessly with existing backup technologies—no rip-and-replace required—and offers continuous validation, giving organizations ongoing proof of cyber readiness rather than unpleasant surprises when disaster strikes.

Ransomware Recovery as a Managed Discipline

The enhanced RRaaS platform is more than a safety net—it’s a cyber recovery ecosystem that combines proactive defense and orchestrated restoration. Its core features include:

• Gap assessment and disaster recovery planning

• Immutable, air-gapped backups

• AI-driven backup scanning and validation

• Cleanroom testing and hot-site failover

• Automated recovery orchestration and runbook management

• Real-time resilience dashboards for visibility

The approach reflects a growing consensus among enterprise CISOs: cyber resilience is not just about restoring data—it’s about restoring trust.

With AI-backed assurance, Recovery Point is positioning its RRaaS platform as the gold standard for enterprises seeking to prove that their backups—and business operations—can stand up to the next wave of ransomware.

Get in touch with our MarTech Experts.

At Advertising Week, Ryff unveiled what could become one of the most transformative analytics tools for advertisers and creators alike: Scene Intelligence™, a new AI-powered framework designed to understand how humans actually respond to visual content—beyond surface-level metrics like views and impressions.

Developed over three years and trained on hundreds of thousands of entertainment records, Scene Intelligence promises to bridge a long-standing blind spot in media measurement—helping marketers answer why content drives engagement and how it influences decisions like brand consideration or purchase intent.

“Scene Intelligence doesn’t just measure how many people watch or how they feel,” said Roy Taylor, Founder of Ryff. “It helps us understand why—and what kind of content drives action. This moves creative and marketing decisions away from guesswork and grounds them in science.”

Beyond Views: The Science of the Scene

For decades, the $600 billion entertainment and advertising ecosystem has relied on metrics that show reach—but not reaction. Scene Intelligence shifts that paradigm by analyzing over 2,000 visual attributes per scene, from object placement and composition to character interaction and pacing.

Using its proprietary Behavioral Environmental Descriptors (BEDs), the system generates four new metrics:

• Scene Prominence Score (SPS) – measures visibility and impact of on-screen elements.

• Scene Weighted Impact Score (SWIS) – evaluates overall influence across a full program.

• Scene Consideration Potential (SCP) – predicts likelihood of brand consideration after viewing.

• Purchase Pathway Score (PPS) – forecasts consumer actions post-exposure.

In early pilots, Ryff reports results that would make any brand strategist take notice:

• 95% model accuracy across platforms

• 45% boost in brand integration effectiveness

• 3.2x increase in purchase intent when content is optimized through Scene Intelligence insights

AI on the Cloud, Analytics in Real Time

Built on Oracle Cloud Infrastructure, the system leverages Ryff’s ALGO-C (content classification) and ALGO-D (behavioral prediction) models to process massive entertainment datasets in real time. Its ViewStream Intelligence™ module adds live viewership analytics across streaming and broadcast platforms—allowing brands to tweak campaigns mid-flight through a single, unified dashboard.

The tool will be available in three formats:

• Enterprise API for studios and streaming platforms

• Brand Intelligence Suite for agencies and advertisers

• Creator Analytics for production companies and individual creators

Early adopters will also gain access to historical content analysis, predictive modeling for new releases, and competitive intelligence tailored to their industry.

Why It Matters

As the streaming market races toward $1.2 trillion by 2027 and video ad spend nears $450 billion, the ability to decode why audiences connect with certain scenes—and how that translates into commercial action—could redefine entertainment marketing strategy.

Scene Intelligence positions Ryff at the intersection of AI, psychology, and creative optimization. In an age when brands are fighting to hold viewer attention across fragmented channels, this kind of visibility into the emotional mechanics of content could become the new metric that matters.

At Advertising Week, Ryff unveiled what could become one of the most transformative analytics tools for advertisers and creators alike: Scene Intelligence™, a new AI-powered framework designed to understand how humans actually respond to visual content—beyond surface-level metrics like views and impressions.

Developed over three years and trained on hundreds of thousands of entertainment records, Scene Intelligence promises to bridge a long-standing blind spot in media measurement—helping marketers answer why content drives engagement and how it influences decisions like brand consideration or purchase intent.

“Scene Intelligence doesn’t just measure how many people watch or how they feel,” said Roy Taylor, Founder of Ryff. “It helps us understand why—and what kind of content drives action. This moves creative and marketing decisions away from guesswork and grounds them in science.”

Beyond Views: The Science of the Scene

For decades, the $600 billion entertainment and advertising ecosystem has relied on metrics that show reach—but not reaction. Scene Intelligence shifts that paradigm by analyzing over 2,000 visual attributes per scene, from object placement and composition to character interaction and pacing.

Using its proprietary Behavioral Environmental Descriptors (BEDs), the system generates four new metrics:

• Scene Prominence Score (SPS) – measures visibility and impact of on-screen elements.

• Scene Weighted Impact Score (SWIS) – evaluates overall influence across a full program.

• Scene Consideration Potential (SCP) – predicts likelihood of brand consideration after viewing.

• Purchase Pathway Score (PPS) – forecasts consumer actions post-exposure.

In early pilots, Ryff reports results that would make any brand strategist take notice:

• 95% model accuracy across platforms

• 45% boost in brand integration effectiveness

• 3.2x increase in purchase intent when content is optimized through Scene Intelligence insights

AI on the Cloud, Analytics in Real Time

Built on Oracle Cloud Infrastructure, the system leverages Ryff’s ALGO-C (content classification) and ALGO-D (behavioral prediction) models to process massive entertainment datasets in real time. Its ViewStream Intelligence™ module adds live viewership analytics across streaming and broadcast platforms—allowing brands to tweak campaigns mid-flight through a single, unified dashboard.

The tool will be available in three formats:

• Enterprise API for studios and streaming platforms

• Brand Intelligence Suite for agencies and advertisers

• Creator Analytics for production companies and individual creators

Early adopters will also gain access to historical content analysis, predictive modeling for new releases, and competitive intelligence tailored to their industry.

Why It Matters

As the streaming market races toward $1.2 trillion by 2027 and video ad spend nears $450 billion, the ability to decode why audiences connect with certain scenes—and how that translates into commercial action—could redefine entertainment marketing strategy.

Scene Intelligence positions Ryff at the intersection of AI, psychology, and creative optimization. In an age when brands are fighting to hold viewer attention across fragmented channels, this kind of visibility into the emotional mechanics of content could become the new metric that matters.

Get in touch with our MarTech Experts.