Enterprise sales teams often rely on CRM systems that are packed with mid-level contacts—but missing the executives who actually approve deals. A new integration between ExecAtlas and SalesIntel aims to close that gap.

Announced by Equilar, the partnership combines executive intelligence data from ExecAtlas with SalesIntel’s signal-based buying committee insights and verified contact data. The result is a unified system that enriches Salesforce records with executive-level profiles, verified contact details, and relationship mapping designed to help sales teams reach decision-makers faster.

The integration targets a common problem in enterprise sales: incomplete CRM data that makes it difficult to identify and engage the real buying committee behind large deals.

Filling the Executive Data Gap in CRMs

Most CRM systems contain detailed account records but often lack accurate profiles for C-suite leaders or board-level decision-makers.

That creates friction for go-to-market teams attempting to close enterprise deals, where purchasing decisions typically involve multiple senior executives across departments.

According to David Chun, the integration was designed to address exactly that issue.

“Most Salesforce instances are missing the executives who actually make buying decisions,” Chun said. “Sales teams have account records and mid-level contacts, but the C-suite profiles are incomplete, outdated, or absent entirely.”

ExecAtlas aims to solve that problem by automatically populating missing executive profiles inside Salesforce while keeping leadership records updated as executives move between roles.

Combining Signals With Relationship Intelligence

While ExecAtlas focuses on executive-level intelligence, SalesIntel brings a complementary capability: identifying the right moment to reach out.

The company’s platform uses signal-driven data—including intent signals and engagement triggers—to help sales teams determine when prospects are most likely to be evaluating solutions.

By combining that signal intelligence with ExecAtlas’s executive data, the integration gives sales teams a more complete view of enterprise buying dynamics.

“Knowing who to call is only half the battle,” said Manoj Ramnani. “Knowing when, why, and who can open the door is how enterprise deals actually get closed.”

The combined platform allows sales teams to identify key executives, monitor engagement signals, and uncover internal relationships that could enable warm introductions.

Four Capabilities Designed for Enterprise Sales

The integrated system delivers several features aimed at improving enterprise deal execution.

1. Complete Executive Coverage

ExecAtlas enriches CRM records with missing executives at target accounts, including C-suite leaders and senior decision-makers. This ensures sales teams see the full buying committee rather than just the contacts already stored in the CRM.

2. Verified Contact Information

SalesIntel adds AI- and human-verified contact data—including email addresses and mobile numbers—to executive profiles. The company claims accuracy rates of up to 95%, helping teams reduce bounce rates and manual research.

3. Relationship Intelligence

ExecAtlas maps connections between executives based on shared work history, board affiliations, and professional networks. This reveals potential introduction paths within an organization that can help sales teams build trust with decision-makers.

4. Real-Time Executive Tracking

Leadership changes are tracked daily, ensuring that CRM records remain current when executives change roles or move to new companies. That visibility can trigger new engagement opportunities for sales teams.

Why CRM Data Accuracy Is Becoming Critical

The integration arrives at a time when B2B sales teams are under increasing pressure to operate with more precision.

Enterprise deals now involve complex buying committees, longer sales cycles, and multiple decision-makers across departments. Without accurate data, sales teams often spend significant time researching contacts and verifying information before they can even begin meaningful engagement.

At the same time, modern go-to-market strategies increasingly rely on multi-threaded outreach—engaging several stakeholders within a company simultaneously.

That strategy only works if sales teams can quickly identify the right executives and connect with them directly.

By combining executive intelligence with verified contact data and engagement signals, the ExecAtlas–SalesIntel integration aims to streamline that process.

The Bigger Trend: Data-Rich Sales Workflows

The partnership also reflects a broader shift in the sales technology landscape.

Sales teams are moving away from static contact databases toward dynamic intelligence platforms that combine multiple layers of insight:

• Contact verification

• Buying signals and intent data

• Relationship mapping

• CRM enrichment

• Real-time leadership tracking

Together, these capabilities help go-to-market teams operate with more context and precision throughout the sales cycle.

For organizations pursuing large enterprise deals, the ability to identify decision-makers early—and engage them with relevant timing and context—can significantly improve win rates.

With the new integration, ExecAtlas and SalesIntel are betting that the future of enterprise selling depends less on simply having data, and more on having the right data connected directly to the workflow where deals happen.

Get in touch with our MarTech Experts.

The race to build richer business intelligence datasets just took a major step forward.

OpenData.org has released a massive U.S. business dataset containing 86 million organizations, 101 million contacts, and 142 million locations, creating one of the most comprehensive open datasets mapping the American corporate ecosystem.

The release becomes even more notable through a strategic partnership with Senzing, which provides built-in AI-powered entity resolution capabilities designed to clean, match, and unify records across datasets.

Delivered in Senzing-ready JSON format, the dataset allows organizations to immediately integrate high-volume business intelligence data into analytics, compliance, and AI pipelines.

In short: OpenData.org is trying to do for organizational data what open knowledge graphs did for the web—create a structured map of how businesses, people, and locations connect.

Mapping the U.S. Business Ecosystem

At its core, the dataset functions as a large-scale entity graph linking companies, executives, and operational locations.

The release includes:

• 86 million organizations

• 101 million people-to-company relationships

• 142 million business locations

These connections allow users to move beyond static company records and instead analyze relationships across the business ecosystem.

Each organization is connected to multiple locations such as headquarters, branch offices, operational facilities, and registered addresses. Meanwhile, more than 101 million contacts link individuals to the organizations they control or operate.

That structure makes it possible to trace corporate hierarchies, discover shared executives across companies, and map operational footprints.

For analysts, investigators, and sales teams, that kind of relational data can provide critical context that traditional company databases often lack.

Built From Government Data at National Scale

The dataset was assembled from filings and records across 100,000+ U.S. government agencies, including:

• Internal Revenue Service

• U.S. Department of Labor

• U.S. Securities and Exchange Commission

• Small Business Administration

• United States Postal Service

The dataset also incorporates state and local regulatory filings, creating a far broader coverage base than most commercial corporate data providers, which often focus heavily on public companies.

Another key element: the inclusion of 162 reference identifiers used across financial, regulatory, and geographic datasets.

These identifiers include global and financial standards such as:

• Legal Entity Identifier (LEI)

• Financial Instrument Global Identifier (FIGI)

• International Securities Identification Number (ISIN)

• Placekey

The result is a dataset designed to act as a cross-reference layer, enabling organizations to match and connect multiple external data sources.

AI-Powered Entity Resolution From Senzing

Large-scale datasets are only useful if records can be accurately matched across sources—a notoriously difficult problem known as entity resolution.

That’s where the partnership with Senzing comes in.

Senzing’s technology uses a combination of machine learning and rule-based logic to determine whether two records represent the same real-world entity—even when names, addresses, or identifiers vary.

The system relies on the company’s Entity Centric Learning architecture, which continuously improves how entities are matched and resolved across datasets.

According to Jeff Jonas, the integration enables organizations to quickly identify relationships and data inconsistencies without building complex matching systems themselves.

“Organizations using the OpenData.org dataset can immediately benefit from Senzing’s entity resolution technology,” Jonas said, noting that the system can detect hidden relationships and reconcile duplicate records in real time.

Another key differentiator: the platform can run locally without requiring sensitive data to be uploaded to the cloud—an important factor for compliance-heavy industries.

Why Entity Graphs Are Becoming Strategic Data Infrastructure

Datasets like OpenData.org’s reflect a growing shift toward entity graph architectures in enterprise data management.

Instead of storing isolated records—like a single company profile—entity graphs focus on the relationships connecting entities.

That approach has become increasingly important for applications such as:

• Financial compliance and AML investigations

• Know Your Customer (KYC) and Know Your Business (KYB) verification

• Fraud detection and risk monitoring

• Investment research and due diligence

• CRM enrichment and B2B lead generation

• AI model training and analytics

In many of these scenarios, the most valuable insight lies not in the individual record but in the connections between records.

For example:

• Multiple companies sharing the same executive

• Businesses operating from the same physical address

• Ownership structures spanning multiple corporate entities

Without an entity graph, uncovering those connections often requires manual research across dozens of fragmented databases.

An “Open Rosetta Stone” for Organizational Data

For Jose M. Plehn, the goal of the project is to create an open infrastructure layer for business intelligence.

Plehn argues that despite the explosion of corporate data platforms, there has been no truly open dataset covering the full spectrum of organizations beyond public companies.

“Every transaction, relationship, and risk assessment connects back to an organization, person, or location,” he said.

He compares the dataset to a “Rosetta Stone” for business data, providing a shared set of identifiers and relationships that allow different datasets to interoperate.

If that vision holds, OpenData.org’s release could become a foundational resource for industries ranging from financial services to marketing technology.

The Bigger Picture: Data Graphs Powering AI and Analytics

The launch also reflects a broader trend across the data industry.

As AI systems and analytics platforms increasingly depend on large, structured datasets, entity graphs are becoming foundational infrastructure.

Companies building AI-driven applications—from fraud detection systems to GTM intelligence platforms—require datasets that connect people, organizations, and locations at scale.

By combining open-source coverage, government-sourced records, and built-in entity resolution, OpenData.org’s dataset aims to position itself as a key building block in that emerging ecosystem.

Whether it becomes a standard reference layer for business data remains to be seen—but with hundreds of millions of linked entities already mapped, the project is starting with a significant head start.

Get in touch with our MarTech Experts.

Global ecommerce accelerator Pattern Group Inc. delivered a record-breaking year in 2025, posting $2.5 billion in annual revenue, up 39% year over year, as brands increasingly rely on its AI-powered platform to navigate the complex world of global digital marketplaces.

The company’s strong performance highlights a growing shift in ecommerce: brands are outsourcing marketplace execution—from logistics to digital marketing—to specialized technology platforms that can manage the entire retail lifecycle.

For Pattern, that strategy appears to be paying off.

A Record Quarter Caps a Breakout Year

Pattern closed the year with a strong fourth quarter, reporting $723 million in revenue, a 40% year-over-year increase.

The company also reported several additional milestones for the quarter:

• Net income: $29 million, up 58% year over year

• Adjusted EBITDA: $43 million, up 59%

• International revenue: $94 million, up 69%

• Non-Amazon revenue: $61 million, up 94%

One key metric investors watch closely—net revenue retention (NRR)—also reached a record 124%, meaning existing brand partners increased their spending significantly year over year.

For marketplace platforms, strong NRR often signals deep customer relationships and growing reliance on the platform’s services.

“2025 was a defining year for Pattern,” said Dave Wright. “We delivered record results, exceeding our prior expectations and demonstrating our ability to scale with discipline.”

A Different Kind of Ecommerce Platform

Unlike traditional software platforms that simply provide tools to brands, Pattern operates closer to a full-stack ecommerce operator.

The company’s model combines:

• Proprietary marketplace technology

• Global logistics infrastructure

• Data and AI-driven marketplace optimization

• Direct inventory ownership

That last element is particularly notable.

Because Pattern often owns the inventory it sells on marketplaces, its revenue is tied directly to product sales rather than SaaS subscription fees.

“Our platform is built to optimize the ecommerce equation and connect brands to consumers wherever they shop,” Wright said. “We are not simply enabling commerce—we are executing it end-to-end.”

This model aligns Pattern’s financial performance closely with the success of the brands it represents.

Expanding Beyond Amazon

A major theme in Pattern’s 2025 results is diversification beyond Amazon, long the dominant platform for third-party marketplace sellers.

Revenue not attributable to Amazon reached $183 million for the year, representing 60% growth.

That reflects increasing activity across alternative marketplaces, including regional ecommerce platforms and retail marketplaces worldwide.

Marketplace diversification has become a strategic priority for brands looking to reduce dependence on a single ecommerce ecosystem.

Pattern’s platform helps brands manage that complexity by consolidating marketplace operations—product listings, advertising, pricing, and logistics—into a single system.

Global Expansion Accelerates

International growth also played a significant role in the company’s performance.

Pattern reported $266 million in international revenue for 2025, up 63% year over year.

As ecommerce marketplaces proliferate across regions—including Asia, Europe, and Latin America—brands increasingly need localized strategies to compete effectively.

Pattern’s global infrastructure is designed to help brands navigate these regional ecosystems without building their own international operations from scratch.

For many consumer brands, that approach offers a faster route to global digital expansion.

Profitability and Cash Flow Improve

Despite rapid growth, Pattern continued to expand profitability.

For the full year 2025, the company reported:

• Adjusted EBITDA: $153 million, up 52%

• Operating cash flow: $99 million, up 41%

• Free cash flow: $79 million, up 58%

Net income for the year totaled $16 million, lower than the prior year’s $68 million. The decline was largely due to $104 million in stock-based compensation related to the company’s IPO earlier in 2025.

Even with those costs, Pattern maintained strong operating performance.

Looking Ahead: Another Growth Year

Pattern expects growth to continue in 2026.

For the first quarter of 2026, the company forecasts:

• Revenue between $710 million and $720 million

• Adjusted EBITDA between $41 million and $42 million

For the full year 2026, Pattern anticipates:

• Revenue between $3.12 billion and $3.16 billion

• Adjusted EBITDA between $180 million and $182 million

Those projections imply 25% to 26% revenue growth for the year.

According to Jason Beesley, the company’s growth will continue to come from three primary areas: expanding partnerships with existing brands, adding new brand partners, and increasing marketplace diversification.

Share Buyback Signals Confidence

Alongside its earnings report, Pattern also announced a $100 million share repurchase program authorized by its board of directors.

The program allows the company to buy back shares of its Series A common stock through open market purchases or private transactions.

The move is often interpreted by investors as a signal that leadership believes the company’s stock is undervalued or that future cash flow will remain strong.

The Bigger Trend: Marketplace Commerce Is Getting Complicated

Pattern’s strong results reflect a broader shift across ecommerce.

As online marketplaces multiply, brands face an increasingly complex ecosystem that includes:

• Global marketplaces

• Retail media advertising platforms

• Cross-border logistics networks

• Regional regulatory environments

Managing those moving parts internally can be difficult and expensive.

As a result, many brands are turning to specialized marketplace operators like Pattern that combine software, logistics, and operational expertise.

In many ways, these platforms are becoming the outsourced infrastructure of global ecommerce.

If Pattern’s growth trajectory continues, it may signal that the future of marketplace commerce isn’t just about selling products online—but about managing the complex systems behind them.

Get in touch with our MarTech Experts.

In a crowded field of sales tech giants, Consensus, the AI-powered demo automation platform, has earned a spot in G2’s Top 5 Sales Software companies for 2026 — standing out as the only demo automation platform recognized alongside Salesforce, HubSpot, Gong, and PandaDoc.

This nod isn’t just a trophy. It signals the arrival of Demo-Led Growth as a legitimate GTM strategy. While Salesforce defined CRM, HubSpot made inbound marketing ubiquitous, and Gong brought conversation intelligence into the mainstream, Consensus is pioneering a new category: always-on, intelligent demos that sell for you.

Consensus allows revenue teams to deliver interactive demos 24/7. Each session captures deep buyer intent and stakeholder data — who watched, what they engaged with, and who they shared it with. That intelligence feeds directly to sales reps, giving them a precise roadmap to close deals faster.

"Demo automation has been the best-kept secret of winning GTM teams for years," said Betty Mok, SVP of Marketing at Consensus. "Being named alongside Salesforce, Gong, and HubSpot isn’t a badge — it’s a signal that Demo-Led Growth separates winners from everyone else."

Unlike traditional sales processes that rely on rep availability and performance, Consensus scales demo delivery without sacrificing insight. Users report measurable improvements in engagement, demo completion rates, and pipeline velocity — a clear indication that automated, intent-driven demos can accelerate conversion in ways static presentations never could.

Industry analysts see this as part of a broader shift in B2B sales tech. Companies are moving beyond one-off demos or static content. Platforms like Consensus provide dynamic, data-rich buyer experiences that link marketing intent directly to sales outcomes. In other words, the era of hoping your reps deliver a perfect demo every time is over. The era of intelligent, scalable, 24/7 demo experiences is officially here.

For GTM teams, this recognition from G2 could mark a turning point. As more organizations adopt Demo-Led Growth, the tech landscape may start to look less like a collection of isolated tools and more like integrated, experience-first revenue platforms — with Consensus leading the charge.

Get in touch with our MarTech Experts.

Guideline, a leading provider of Ad Intelligence and Media Plan Management technology, has unveiled its Media Plan Management MCP Server, a new product that allows advertising agencies, media buyers, and enterprise clients to connect their own AI agents directly to Guideline’s platform. Built on the Model Context Protocol (MCP) — the emerging open standard for agentic AI connectivity — the server is the first in a planned series of MCP-enabled capabilities from the company.

Traditionally, media planning has been a patchwork of disconnected systems, with teams manually exporting data and compiling reports across multiple platforms. As campaigns grow in complexity across markets and channels, the need for faster, integrated workflows has become urgent. The MCP Server addresses this by offering a plug-and-play connection between any MCP-compatible AI agent — whether Claude, ChatGPT, or proprietary internal tools — and Guideline’s media plan management suite, no custom integration required.

Once connected, planners and buyers can interact with media plans conversationally, asking natural-language questions about campaign status, budgets, vendor performance, or plan-to-actual comparisons. The AI agent can instantly provide actionable insights, consolidate multi-campaign data, and generate performance summaries — all without leaving the chat interface. The server provides secure, read-only access, ensuring sensitive data remains protected.

“The complexity of modern media planning is skyrocketing, and agencies are increasingly turning to AI to manage it,” said Vincent Mifsud, CEO of Guideline. “Our MCP Server positions Guideline at the center of this transformation, giving clients AI-native infrastructure to streamline workflows, make faster decisions, and focus human talent on strategy rather than manual processes.”

The MCP standard, originally developed by Anthropic and now supported by OpenAI, Google, and Microsoft, has become a widely adopted framework for connecting AI agents to external tools. Analysts project that 75% of enterprise gateway vendors will integrate MCP by the end of 2026. By building on this open standard, Guideline ensures broad compatibility and future-proof connectivity.

Steve Silvers, Guideline’s Chief Product Officer, called the launch a “pivotal moment” in the company’s agentic AI strategy, highlighting that the MCP Server is just the first of several AI-native capabilities planned across the media plan management suite. The goal: allow agencies and brands to deploy AI agents across every stage of media planning and buying without traditional integration headaches.

For agencies, the implications are significant. Instead of toggling between platforms, manually compiling reports, or waiting for analytics cycles, planners can engage AI agents in multi-step analysis, retrieving, consolidating, and interpreting media plan data across campaigns, clients, and markets — all in a single conversational workflow.

With AI-driven workflows now integrated into the media planning backbone, Guideline is betting that

agentic AI will become as essential to agencies as spreadsheets once were, redefining how marketing operations teams plan, execute, and optimize campaigns.

Get in touch with our MarTech Experts.

Three leading luxury marketing firms — North & Warren, the digital and media powerhouse; Quinn, the award-winning strategic communications agency; and Interluxe Group, a leader in brand experiences and in-person activations — have officially merged under the Interluxe Group brand. The integration forms a full-service, luxury-focused marketing agency that combines proprietary audience data with media, communications, digital marketing, and experiential solutions.

The unified Interluxe Group aims to provide luxury brands with precision targeting and creative execution across earned media, performance marketing, experiential activations, and strategic communications. By connecting data-driven insights with immersive storytelling, the agency promises to help brands drive acquisition, loyalty, engagement, and advocacy — all with measurable outcomes.

“Our merger simplifies complexity for luxury brands while expanding possibilities across media, communications, and experiential,” said Nick Van Sicklen, Founder & CEO of Interluxe Group. “This integration allows us to deliver both scale and craft with measurable results.”

The newly combined agency now boasts 130+ team members across North America and Europe, led by an experienced executive team: Nick Van Sicklen (Founder & CEO), Matt Carroll (Founder & Chief Commercial Officer), Maneesh K. Goyal (President, Experiential & Executive Chairman), Jay Meyer (President, Lifestyle Media), and Florence Quinn (President, Strategic Communications).

“Experiences sit at the heart of how luxury brands build emotional connection and long-term loyalty,” said Maneesh K. Goyal. “This unified platform allows us to seamlessly connect storytelling, media, and live experiences in a way that feels intentional and immersive.”

The merger builds on Interluxe Group’s vision of a modern, full-service agency purpose-built for luxury brands seeking to engage high-net-worth audiences effectively. By combining strategic communications, digital marketing, and live experiences within a single ecosystem, the agency positions itself as a go-to partner for brands across travel, hospitality, automotive, fashion, jewelry, beauty, and home design sectors.

Supporting this expansion, Interluxe Group received a strategic investment in January 2025 from Mountaingate Capital, a Colorado-based private equity firm, aimed at fueling growth and solidifying the agency’s leadership in the luxury marketing space.

“Integrating under the Interluxe Group brand allows us to deliver best-in-class solutions with cohesion and a seamless way for luxury brands to connect with their most valuable audiences,” added Matt Carroll, Founder & Chief Commercial Officer.

With this merger, Interluxe Group seeks to redefine how luxury brands engage with affluent audiences, combining intelligence, creativity, and immersive experiences in one unified platform — a model likely to influence the next wave of luxury marketing strategy.

Get in touch with our MarTech Experts.

PulsePoint, the technology company reshaping health marketing, has expanded its omnichannel capabilities with a new integration on Reddit, enabling healthcare marketers to target healthcare professionals (HCPs) directly while coordinating campaigns across PulsePoint’s full ecosystem.

The move taps into a growing trend: HCPs increasingly engage on social platforms to connect with peers, discuss clinical questions, and consume educational content. With PulsePoint’s Audience Manager, marketers can build dynamic, verified HCP segments based on clinical intent, digital interests, and brand relevance — then activate them seamlessly on Reddit.

Campaigns on Reddit through PulsePoint offer:

• Self-serve activation in a high-engagement social channel used by a broad U.S. HCP audience

• Omnichannel orchestration, connecting Reddit campaigns with programmatic display, EHR platforms, DOOH, and other social channels

• NPI-level measurement, providing actionable insights including profession, referral source, and detailed site activity

• Optimized audience intelligence, improving social ROI and campaign outcomes

“Healthcare professionals are increasingly turning to community platforms to explore clinical topics, evaluate new therapies, and engage in peer-to-peer discussion,” said Ezra Suveyke, Chief Product Officer at PulsePoint. “This integration gives brands the ability to engage HCPs on Reddit in a way that’s informed by their behavior across all channels.”

PulsePoint’s timing is strategic. In Q4 2025, daily active users on Reddit rose 19% year over year, with views on health topics up 61% year over year. Clinically focused communities such as r/medicine provide fertile ground for professionals staying informed, sharing insights, and debating trends.

For marketers seeking more than standard social metrics, PulsePoint offers HCP365, which delivers granular, NPI-specific insights across channels — from site visits and search activity to email engagement — providing a comprehensive picture of HCP behavior and campaign impact.

With Reddit now in the mix, PulsePoint positions itself as a go-to platform for healthcare brands seeking to combine precise HCP targeting with full omnichannel visibility, ensuring campaigns are both measurable and meaningful.

Get in touch with our MarTech Experts.

Tata Elxsi, a global leader in design and technology services, has launched DevStudio.ai, a multi-agent AI solution designed to accelerate the automotive software development lifecycle (SDLC) for OEMs, Tier-1 suppliers, and semiconductor companies. Purpose-built for automotive engineering, the platform addresses the complexity, safety, and compliance demands unique to the industry.

Unlike general-purpose generative AI tools, DevStudio.ai is ASPICE-aligned and supports all stages of the V-cycle, from requirements and architecture to implementation, testing, and qualification. The platform maintains end-to-end traceability and integrates with widely used engineering toolchains, allowing teams to embed AI “co-engineers” directly into existing workflows.

A standout feature is DevStudio.ai’s deployment flexibility: it operates on both cloud-based infrastructure and air-gapped on-premise environments, ensuring compliance with enterprise AI and security policies.

“The automotive industry is at an inflection point,” said Sundar Ganapathi, CTO – Automotive, Tata Elxsi. “Competitive pressures now demand software development at China speed. DevStudio.ai brings the power of generative AI into the automotive SDLC, enabling OEMs and suppliers to accelerate development while maintaining the rigor required for safety-critical systems.”

Early deployments of DevStudio.ai are already underway in North America, Japan, and India, spanning body, chassis, infotainment, and software-defined vehicle (SDV) architectures. Early results indicate noticeable speed-to-market improvements and productivity gains, validating the platform’s design for automotive-specific challenges.

Pallavi Dalal, Head – Automotive GenAI and AI Practice at Tata Elxsi, added, “DevStudio.ai is the culmination of intensive collaboration between our automotive domain experts and generative AI specialists. Our vision is an AI co-engineer working alongside every engineer, from OEMs to Tier-1 suppliers. By partnering with leading GenAI companies and hyperscalers, we’re building a future-forward platform for automotive engineering.”

With the launch of DevStudio.ai, Tata Elxsi positions itself at the forefront of AI-driven automotive innovation, offering a tool that merges generative AI capabilities with the rigorous safety and compliance demands of modern vehicle software development.

Get in touch with our MarTech Experts.