TV advertising is starting to look a lot more like digital, and Harmonic wants to make sure broadcasters aren’t left behind. The company today rolled out a set of enhancements to its VOS360 Ad SaaS solution, introducing AI-powered contextual ad triggers, new programmatic ad workflows for linear TV, and fresh SDKs that expand compatibility with widely used video players.

The pitch is clear: a smoother ad workflow, more revenue potential, and fewer headaches for streamers, content providers, and broadcasters trying to navigate the hybrid world of TV and digital advertising.

AI in the Ad Break: Smarter, Contextual Triggers

Live sports has always been the crown jewel of ad inventory, but it’s also tricky territory—breaks are limited, timing is unpredictable, and a badly timed ad can ruin the viewing experience. Harmonic’s upgrade takes a page from the digital playbook, using AI-driven video analysis to pull scene-level metadata in real time.

That means broadcasters can drop contextually relevant ads—think overlays, L-shapes, or double boxes—precisely when engagement peaks. The result: more premium ad slots without cutting away from the action. For brands, that’s a way to connect with fans mid-game, not just during halftime. For publishers, it’s the promise of higher yields from inventory that was once difficult to monetize.

Bringing Programmatic to Linear TV

If contextual AI is about timing, programmatic is about scale. Harmonic is extending the efficiency of digital ad transactions to traditional linear broadcasting, a sector that’s long been locked into legacy sales processes.

With VOS360 Ad’s new programmatic workflows, broadcasters can now:

• Automate ad buying and selling with DSP and SSP integrations.

• Run unified campaigns across CTV and linear TV from a single system.

• Tap into new demand sources via platforms like Google Ad Manager and Magnite SpringServe.

This shift could be a big deal for broadcasters who’ve been struggling to keep pace with CTV’s flexibility. By marrying broadcast reach with programmatic efficiency, Harmonic is positioning linear TV as a viable player in the digital ad economy.

The TV ad market is in flux. CTV ad spend is climbing rapidly, but broadcasters still hold sway over live events, sports, and news—categories that command premium dollars. The challenge has always been bridging the gap between old-school broadcast workflows and the fast-moving, data-driven world of programmatic digital.

Harmonic’s VOS360 Ad SaaS upgrades suggest that gap is closing. If the execution lives up to the promise, broadcasters could unlock entirely new revenue streams without ripping out their infrastructure. And for advertisers, that means the elusive promise of unified, cross-platform campaigns gets one step closer to reality.

As Gil Rudge, SVP at Harmonic, put it: “From smarter, real-time ad placement to unified programmatic campaigns across CTV and broadcast, we’re giving customers the innovations they need to thrive.”

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Car dealerships may finally get the personalization muscle e-commerce giants have enjoyed for years. Fullpath, the AI-first Customer Data Platform (CDP) built for the automotive industry, has acquired Fuse Autotech’s Dynamic Payments solution—a move designed to help dealerships deliver real-time, personalized offers across every channel.

The deal signals a shift in how auto retailers manage customer engagement, with data flowing not just into CRMs, but directly into finance, service, and sales workflows in real time.

From Sticker Price to Smart Price

At its core, Dynamic Payments pulls pricing, rebates, OEM incentives, financing rates, and dealership-specific promos straight into the Fullpath CDP. That means every offer—whether it appears on a dealership website, in an email, an SMS, or a digital ad—is based on live inventory and up-to-the-minute deals.

For shoppers, it’s a welcome break from the usual “call for price” runaround. For dealers, it’s a way to automate offer generation and reduce friction at every stage of the buying process.

Fullpath CEO Aharon Horwitz put it bluntly: “This integration supports every profit center at the dealership—from sales and finance to service and parts—by ensuring marketing activities are always tied to real data.”

A New Layer of Personalization

The real trick here is scale. Traditional auto marketing often relied on broad campaigns with static incentives. By contrast, Fullpath’s expanded ecosystem can now push tailored offers instantly across multiple touchpoints.

• Websites: inventory pages that reflect real pricing and incentives.

• Email & SMS: personalized deals sent with zero manual input.

• Ads: dynamically updated campaigns that match real inventory.

For Andrew Walser, CEO of Walser Automotive, the payoff is tangible: “With real-time, personalized offers integrated into Fullpath’s platform, we’ve significantly increased closing rates and reinforced loyalty.”

The automotive sector is racing to modernize its digital retailing. Customers accustomed to Amazon-style personalization don’t have patience for outdated lead forms or static pricing. Competitors like Tekion and Roadster have been pushing digital-first platforms, but Fullpath’s acquisition of Fuse Dynamic Payments shows a different angle: make the CDP the control center of the dealership.

If it works as promised, this could streamline dealer marketing while finally delivering the frictionless buying experience car shoppers have been promised for years. The question now is whether other CDP players in automotive—or even broader retail verticals—follow suit.

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Financial fraud has always evolved with technology, but the rise of generative AI has supercharged the arms race. Enter Mitek Systems, the NASDAQ-listed identity verification firm, which just picked up a silver medal in Datos Insights’ 2025 Fraud and AML Impact Awards for its work in digital identity defense. The recognition goes to Digital Fraud Defender, Mitek’s security suite engineered to block the latest wave of AI-powered fraud—everything from deepfakes to synthetic IDs to injection attacks.

Traditional fraud detection often leaned heavily on “liveness” checks—making sure a selfie was from a real human, in real time. But as deepfake tech matures, those methods fall short. Mitek’s bet is that the only way forward is multi-layered protection.

Digital Fraud Defender’s toolkit includes:

• Deepfake detection using both visual artifacts and metadata analysis.

• Injection attack detection to spot manipulated or unauthorized video streams.

• Template attack detection that flags patterns tied to recycled fake documents.

• Purple Team adversarial testing, where ethical hackers stress-test the system to anticipate real-world threats.

It’s a mix of machine learning, metadata scrutiny, and proactive red teaming—a layered defense aimed at keeping fraudsters a step behind.

Battle-Tested in the Wild

The tech isn’t just theory. Mitek says Digital Fraud Defender has already exposed high-volume fraud campaigns that slipped past traditional filters. In one phishing-driven attack, the system caught 3,000+ injection attempts before they reached customers. In another, it kept a 99% biometric verification pass rate while filtering out AI-generated imposters.

That balance—catching bad actors without frustrating legitimate users—is key. Too much friction and customers walk. Too little, and the fraud bill spikes.

Industry Context: Deepfakes Meet Finance

Generative AI tools have made it alarmingly easy to spin up convincing fake IDs, manipulated documents, and cloned faces. For financial institutions, the risk is existential: onboarding one synthetic identity can lead to cascading fraud across accounts, loans, and payment rails.

Datos Insights’ Jim Mortensen summed it up: “Organizations can no longer rely on single-point solutions when facing increasingly sophisticated attack vectors.”

Translation: if your fraud prevention strategy still hinges on a selfie blink test, you’re already behind.

Fraud prevention is becoming as much about anticipation as detection. By combining detection with proactive adversarial testing, Mitek is signaling a shift toward pre-emptive resilience in digital identity.

As Chris Briggs, Mitek’s chief product officer, put it: “Liveness detection alone is not enough. That’s why we’ve layered protections to stay ahead of AI-driven threats. Recognition from Datos Insights validates that this approach is setting a new standard in fraud prevention.”

With fraudsters arming themselves with open-source AI and deepfake kits, solutions like Mitek’s may soon move from “nice-to-have” to baseline requirement. And with regulators increasingly eyeing financial institutions’ ability to handle digital fraud, multilayered defenses could also become a compliance necessity.

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Security operations centers don’t just drown in alerts—they drown in data. With attack surfaces expanding across AI, cloud, SaaS, and on-prem, SOCs are increasingly forced to choose between ballooning SIEM bills or leaving critical telemetry logs on the cutting-room floor. CeTu thinks that’s a false choice.

The company, recognized in Gartner’s Hype Cycle for Security Operations 2025, has made its agentless, no-code SecOps data management platform available on the AWS Marketplace. The move makes procurement easier for enterprise teams while putting unspent AWS credits to work.

The Data Flood Problem

Modern SOCs ingest petabytes of telemetry—from AWS CloudTrail logs to VPC Flow Logs and beyond. Yet the costs of shoving everything into a traditional SIEM often prove unsustainable. Many organizations now skip ingesting key security logs altogether, creating dangerous blind spots.

Onboarding new AI apps doesn’t help, introducing a flood of non-standard log formats that require scarce expertise to normalize and correlate. The result: more complexity, more risk, and slower incident response.

CeTu’s Pitch: AI-Powered Data Pipelines

Instead of treating security data as an expense line, CeTu is reframing it as an opportunity. The platform builds dynamic telemetry pipelines that normalize, filter, enrich, and route logs across destinations—from high-performance SIEMs to cost-friendly Amazon S3 buckets or Amazon Security Lake.

Key features include:

• Automation for the modern SOC: Optimize ingestion across SIEMs, data lakes, and storage to cut costs by as much as 80%.

• Security-aware AI: Continuously monitors for blind spots and data quality issues, turning hidden threats into visible signals.

• No-code workflows: Designed for everyday engineers, enabling time-to-value in days, not months.

• AWS-native procurement: Streamlined billing and compliance, with the option to use AWS credits.

“The SOC is evolving, and CeTu is accelerating that transformation,” said CeTu CEO Omer Schneider. “Security teams shouldn’t have to choose between cutting costs and strengthening defenses. CeTu changes that equation.”

Gartner recently noted that telemetry pipelines have entered the “early mainstream” phase of adoption, validating a shift toward smarter data management in cybersecurity. CeTu’s AWS Marketplace debut underscores this trend, positioning it against both pipeline-first vendors like Cribl and broader security analytics players like Splunk.

For enterprises, the appeal is twofold: cut SIEM costs without cutting visibility, and gain a more intelligent defense posture that can adapt to emerging threats like deepfake-driven fraud and AI-powered attacks.

With CeTu now one click away in AWS Marketplace, the pressure is on other SecOps vendors to match its mix of cost efficiency and security-aware intelligence.

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If you thought “process automation” was already running at full throttle, Appian just pressed the turbo button. The company rolled out a batch of AI-driven enhancements designed to make enterprise workflows faster, smarter, and more secure—particularly for data-heavy industries and government customers.

At the heart of this release are four upgrades: semantic smart search, AI availability for self-managed and FedRAMP environments, automatic data fabric scaling, and embedded Process HQ reports. Taken together, they reinforce Appian’s pitch as the platform where AI isn’t just a bolt-on feature but the backbone of how work gets done.

AI Search That Understands You (Not Just Your Keywords)

Forget keyword guessing games. Appian’s upgraded AI smart search uses semantic understanding to return results based on intent, not just exact terms. Tied into the company’s “data fabric,” which unifies millions of records and documents across systems, this makes searching more like asking a colleague who knows where everything is filed. Think fewer dead ends and more context-aware results—useful for customer support cases, underwriting, or any workflow where finding the right detail fast matters.

AI Access for Everyone—Even Government

One of the quieter but more impactful shifts: Appian AI is now fully available in self-managed and FedRAMP environments. Translation? Federal agencies and security-sensitive industries can finally tap into enterprise-grade AI without worrying about compliance roadblocks. In a market where rivals like ServiceNow and IBM are chasing the same contracts, Appian is clearly angling to make itself the “safe bet” for regulated sectors.

Data Fabric That Scales Itself

Enterprise IT teams will appreciate the new data fabric autoscaling. Instead of tweaking capacity by hand, Appian automatically scales to handle heavier query loads. That means high-volume use cases—say, insurance claims or financial risk models—keep running smoothly without admins playing catch-up. Add in asynchronous interface loading (which quietly shuffles slow data into the background), and end users see snappier apps with less lag.

Process Insights Without the IT Bottleneck

Process HQ, Appian’s tool for spotting bottlenecks and inefficiencies, now embeds directly into Appian Sites. End users can explore dashboards, drill down into data, and share insights without calling IT for help. For managers, that means bottleneck-busting insights are just a click away, no tickets required.

Appian’s release isn’t about flashy AI demos—it’s about quietly solving the headaches that make enterprise automation brittle: siloed data, compliance friction, sluggish apps, and reporting bottlenecks. In an environment where CIOs are under pressure to show measurable ROI on AI investments, Appian’s “secure, scalable, and useful” approach could resonate.

Michael Beckley, Appian’s CTO, put it bluntly: “We’re delivering AI with guardrails and transparency, without compromising on security or control.”

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Legacy observability platforms are starting to look like flip phones in a 5G world—functional, but painfully behind the times. Crest Data thinks it has the fix. The company just unveiled its Migration Acceleration Service for Datadog, a new offering designed to slash migration timelines by up to 60%, helping enterprises trade their clunky monitoring stacks for Datadog’s slick, unified observability and security platform.

The observability market has been shifting fast. With cloud-native environments growing more complex, legacy SIEM and monitoring tools often can’t keep up—leaving enterprises paying high costs for underwhelming visibility. Datadog, on the other hand, has steadily become the poster child for modern observability. The hitch? Migrating is usually a nightmare.

That’s where Crest Data steps in. “Many enterprises want to move to Datadog but the migration is slowed by the complexity of converting dashboards, alerts, and workflows from legacy systems,” said Malhar Shah, Crest Data’s Co-founder & CEO. “Our Migration Acceleration Service eliminates that friction.”

How It Works

The service uses a phased approach powered by Crest’s Automated Migration Engine, which automatically converts up to 90% of dashboards, alerts, and workflows into Datadog-native formats. The last 10% gets manual fine-tuning by Crest’s experts—ensuring enterprises don’t end up with half-baked dashboards.

Early adopters say the time savings are real. “What would otherwise have taken several months can now be completed within a few weeks,” said Marylu Velazquez, Sales Director at TecnoMedia, noting that automation not only accelerates the process but also reduces risk and cost.

Datadog itself seems pleased with the partnership. “Helping customers move to Datadog's unified platform while further accelerating migration is a win-win for everyone,” said Jarrod Buckley, VP of Channels & Alliances at Datadog.

Crest’s timing is strategic. As enterprises face pressure to modernize IT infrastructure while trimming budgets, a fast lane to Datadog could be appealing. Rival observability vendors like Splunk and New Relic are also scrambling to show value amid rising competition from Datadog’s all-in-one platform. By positioning itself as the migration enabler, Crest Data isn’t just hitching its wagon to Datadog—it’s putting itself in the middle of one of the hottest tech shifts in enterprise IT.

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Breaking down language barriers has long been a dream in business communications. Krisp, best known for its real-time voice AI, is making that dream far less sci-fi with the launch of AI Voice Translation v2.0. The updated platform introduces a set of heavy-hitting upgrades—Synchronous mode, Auto-scoring, Custom Prompts, and Language Auto-detection—designed to make multilingual conversations faster, smoother, and more human.

If that sounds like a direct shot at the pain points of call centers and global enterprises, that’s because it is.

Real-Time Conversations Without the Lag

At the heart of the upgrade is Synchronous mode, which essentially eliminates the awkward pauses and delays that usually plague translated conversations. Instead of waiting for a third-party interpreter—or worse, fumbling with pre-scripted translations—both sides can now speak in their native language and hear instant translations with minimal lag. Think less “robotic exchange,” more “normal conversation.”

Quality Control, Automated

Manual call sampling for compliance and quality checks has long been a thorn in the side of support teams. Krisp’s Auto-scoring tackles this head-on by automatically evaluating every translated call. That means no more cherry-picked samples, and far fewer compliance slip-ups.

A Smarter, Branded Experience

The platform also lets companies personalize the customer journey through Custom Prompts—pre-recorded, brand-specific intros that keep the tone consistent across markets. Add to that Language Auto-detection, which identifies the customer’s language within seconds, and you have a system designed to make translation feel invisible.

For industries where precision is non-negotiable—say, healthcare, finance, or travel—Krisp introduces Customer Vocabulary, enabling teams to preload domain-specific terms to avoid embarrassing mistranslations. Numbers, IDs, and even sensitive data like PII get handled with an accuracy bump of 5–10 BLEU (Bilingual Evaluation Understudy) points.

Industry Implications

The timing couldn’t be better. According to CMP Research, customers increasingly prefer automated voice interactions, especially when speed and personalization are in play. Krisp’s bet is that real-time translation will shift from a “nice-to-have” to a standard expectation in global contact centers. With support for 80+ languages and enterprise-grade security, Krisp is positioning itself as the go-to for distributed teams and high-volume ops.

Competitors in the space, from Big Tech speech APIs to niche language service providers, may need to rethink their approach. Human interpreters won’t vanish overnight, but when AI can offer instant, natural-sounding, multilingual conversations—without scheduling headaches—businesses will likely take the faster, cheaper route.

As Krisp’s CEO Davit Baghdasaryan put it, this isn’t just about translation. It’s about faster resolutions, stronger relationships, and giving customer support teams superpowers.

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IntelePeer has made its SmartAnalytics platform available on the Microsoft Azure Marketplace, opening up new access for enterprises looking to enhance their conversational AI insights within the Azure ecosystem.

SmartAnalytics, already bundled with IntelePeer’s SmartAgent and SmartOffice solutions, provides real-time data insights, interaction analysis, and compliance monitoring designed to optimize both AI and human customer interactions.

Frank Fawzi, CEO of IntelePeer, called the listing a major milestone. “Being listed in the Microsoft Azure Marketplace makes it easier than ever for customers to access and deploy our SmartAnalytics solution within their existing Azure environments,” he said. “This brings faster time-to-value, simplified procurement, and the ability to scale with confidence on a trusted global platform.”

What SmartAnalytics Delivers

• Performance Dashboard: Offers KPIs like call containment, transfer rates, and interaction durations for quick performance assessments.

• Interaction Explorer: Provides full conversation transcriptions (AI- and human-handled) with advanced search and filtering capabilities.

• Real-Time Insights: Enables custom dashboards for agile, data-driven decision-making.

• Compliance Monitoring: Tracks sentiment, adherence to regulatory frameworks (HIPAA, PCI DSS), and SOP compliance.

• Seamless Integration: Supports Snowflake integration and cross-functional data sharing for broader analytics.

Jake Zborowski, GM of Microsoft Azure Platform, added: “We’re pleased to welcome IntelePeer’s SmartAnalytics solution to the Microsoft Azure Marketplace, which gives our partners great exposure to cloud customers around the globe.”

For businesses, the availability of SmartAnalytics on Azure means streamlined deployment, built-in scalability, and a more holistic view of customer interactions—all without leaving the Microsoft ecosystem.

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