Blog - N28tech

Why Most MedTech AI Pilots Never Reach Production

May 14, 2026 Nithya Konduru

Most MedTech AI pilots do not fail because of the model. They fail because the organization was never operationally ready to scale them. That pattern is becoming increasingly clear across the enterprise AI market:• RAND Corporation estimates that more than 80% of AI projects fail to deliver business value• Gartner reports that only 48% of AI projects make it into production• MIT research found that 95% of generative AI pilots produce no measurable P&L impact, often due to workflow and integration issues rather than model performance The pilot works in a controlled environment:• curated data• dedicated resources• executive attention Production is different. That’s where AI collides with fragmented data, disconnected workflows, unclear ownership, regulatory constraints, and low frontline adoption. At N28 Technologies, we’ve seen the same pattern repeatedly: organizations invest heavily in AI capability while underinvesting in the operational foundation required to support it. That’s the real scaling problem. 1. AI-Ready Data Is Still Rare Most MedTech organizations have data. Few have operationally usable data. Clinical systems, CRM platforms, service data, device telemetry, and commercial operations often live in disconnected environments with inconsistent identifiers and fragmented governance. This is becoming one of the biggest enterprise AI bottlenecks. Gartner has repeatedly identified poor data quality and weak governance as leading causes of AI project failure. A pilot can work around this with curated datasets. Production cannot. At N28 Technologies, we consistently see AI success tied directly to the quality of the operational data layer underneath it. AI scales the quality of your data foundation — good or bad. 2. AI Pilots Ignore Workflow Reality Many AI pilots fail because they are designed outside the operational systems people use every day. Standalone dashboards and disconnected interfaces may work in a pilot environment, but they rarely drive long-term adoption. MIT research on enterprise GenAI deployments found that flawed integration into existing workflows was one of the primary reasons AI projects failed to generate measurable business impact. If AI recommendations are not embedded directly into the workflows teams already trust, usage drops quickly. For MedTech organizations, that means AI must connect directly into systems like Salesforce, Health Cloud, Service workflows, and commercial operations platforms. The organizations scaling AI successfully are designing around workflow execution, not model experimentation. 3. Governance and Ownership Arrive Too Late MedTech organizations often treat governance as a post-pilot exercise when it should shape the architecture from day one. This challenge is becoming more acute as AI regulation expands across healthcare, medical devices, and enterprise software. Gartner recently projected that more than 40% of agentic AI projects could be abandoned due to rising costs, governance gaps, and unclear business value. Regulatory review, auditability, model ownership, retraining processes, escalation paths, and compliance workflows all need to be part of the deployment strategy early. Pilots usually have sponsors. Production systems require operational owners. Without clear ownership, AI systems slowly lose trust, degrade operationally, and eventually disappear from frontline workflows. 4. Success Metrics Focus on Accuracy Instead of Operations A 92% accurate model that nobody operationalizes is still a failed deployment. Too many AI pilots optimize for technical performance while ignoring operational outcomes. The organizations successfully scaling AI are measuring:• reduced cycle times• increased throughput• faster service resolution• improved workflow completion• stronger user adoption Not just model accuracy. This shift matters because enterprise AI is increasingly moving from “insight generation” toward workflow execution. AI only creates enterprise value when it changes operational execution. The Real Question Most MedTech organizations are asking: “Where should we use AI?”The better question is:“What operational foundation does AI need in order to scale?”Because scaling AI is not primarily a model problem.It is a workflow, data, governance, and execution problem.That is where successful deployments are won or lost. At N28 Technologies, we believe the future of enterprise AI is not standalone models or disconnected copilots.It is AI embedded directly into operational workflows where teams already execute work.That requires more than technology. It requires readiness.

Case Studies, AI

Transforming Medicare Advantage Patient Acquisition & Operations with AI + CRM

April 14, 2026 Samir Das

Executive Summary Medicare Advantage (MA) providers face increasing pressure to grow membership, improve patient outcomes, and operate efficiently across distributed care networks. Fragmented systems, manual workflows, and inconsistent patient engagement create bottlenecks that limit both growth and care quality. We worked for a leading Medicare Advantage primary care network to modernize its patient acquisition, engagement, and operational workflows using the Salesforce platform combined with AI-driven automation. The result: 25% faster lead-to-appointment conversion 40% improvement in call center productivity Standardized operations across 160+ care centers This transformation demonstrates how AI + CRM + workflow execution can unlock scalable growth while improving patient experience. The Challenge: Scaling Growth in a Fragmented Ecosystem The client operates a large Medicare Advantage-focused primary care network with over 160 centers. Their growth strategy depends heavily on: Community-based outreach (events, brokers, referrals) Seasonal enrollment cycles (AEP, OEP, SEP, T-65) High-touch patient engagement However, they faced several structural challenges: 1. Disconnected Systems Marketing tools, call center platforms, and EHR systems operated in silos Limited visibility into the patient journey from lead → appointment → care 2. Inefficient Lead Management Manual processes for tracking leads and conversions Delays in routing and follow-up reduced conversion rates 3. Call Center Bottlenecks Lack of real-time performance insights Inefficient routing and scheduling workflows 4. Compliance & Reporting Complexity Increasing regulatory oversight required consistent auditability Reporting was manual and often delayed Our Approach: Workflow Execution at Scale We focussed on workflow execution and not just system implementation. We designed an integrated architecture combining: CRM (Sales Cloud + Service Cloud) Marketing Automation (Marketing Cloud) EHR Integration Call Center Operations AI-driven automation and analytics This created a single, unified system of engagement and execution across the entire patient lifecycle. Solution Architecture 1. Unified Lead-to-Patient Lifecycle We implemented a seamless flow from marketing to care delivery: Lead capture from campaigns, brokers, and events Automated qualification and routing Appointment scheduling and follow-up Conversion into patient records linked to EHR This enabled true end-to-end visibility across: Lead → Qualification → Appointment → First Visit → Ongoing Care 2. Intelligent Marketing & Campaign Execution Using Marketing Cloud, the client was able to: Orchestrate multi-channel campaigns (Email, SMS, outreach) Automate journeys for: AEP / OEP enrollment cycles T-65 prospect nurturing Broker-driven referrals Personalize engagement at scale 3. Optimized Call Center Operations We modernized call center workflows with: Intelligent call routing Real-time agent performance tracking Integrated appointment scheduling Automated follow-ups This turned the call center into a conversion engine, not just a support function. 4. EHR + CRM Integration A tightly integrated EHR ecosystem enabled: Real-time patient data synchronization Visibility into appointment completion and outcomes Improved care coordination This ensured that operational workflows directly supported clinical outcomes. 5. Sales & Commission Automation We introduced: Agent performance tracking Automated commission calculations Insurance verification workflows Documentation validation This reduced administrative burden and improved transparency. 6. Compliance & Governance Layer To support regulatory requirements, we embedded: Audit trails across workflows Risk monitoring and reporting Standardized compliance processes Results & Business Impact The transformation delivered measurable impact across growth, efficiency, and experience: Growth Acceleration 25% faster lead-to-appointment conversion Increased patient acquisition efficiency across all channels Operational Efficiency Standardized workflows across 160+ centers Reduced manual effort in campaign execution and reporting Call Center Transformation 40% improvement in productivity Enhanced reporting accuracy and visibility Data-Driven Decision Making Real-time dashboards across: Campaign performance Conversion funnels Call center metrics Patient journey analytics Why It Worked 1. Workflow Execution Focus We don’t just implement systems—we connect workflows across systems. 2. AI + CRM Integration Combining CRM with AI-driven automation enables: Faster decision-making Reduced manual intervention Scalable personalization 3. Healthcare-Specific Expertise Deep understanding of: Medicare Advantage workflows Enrollment cycles (AEP/OEP) Provider operations and compliance 4. Scalable Architecture Designed to support: Multi-location growth New service lines Future AI capabilities (e.g., AI agents, document processing) Future Opportunities: AI-Driven Healthcare Operations Building on this foundation, organizations can unlock additional value through: AI Agents for Patient Intake Automating document processing (faxes, referrals) Predictive Analytics Identifying high-conversion leads Forecasting capacity and demand Care Journey Automation Proactive engagement based on patient signals Revenue Optimization AI-driven pricing, enrollment targeting, and retention strategies Conclusion Medicare Advantage providers must balance growth, efficiency, and patient experience—all within a complex regulatory environment. This case study demonstrates that with the right combination of: AI CRM Workflow execution Healthcare domain expertise …it is possible to transform fragmented operations into a scalable, high-performing growth engine. About N28 Technologies N28 Technologies is a global AI + Salesforce partner focused on helping organizations modernize operations through intelligent workflow execution. We specialize in: Healthcare & Life Sciences Revenue operations transformation AI agents and automation End-to-end Salesforce implementations With 75+ implementations and deep industry expertise, we help organizations move from automation to execution.

Demo

SDR Agent

January 9, 2026 n28tech

An AI SDR (Sales Development Representative) in Agentforce is an autonomous AI agent integrated with Salesforce that automates top-of-funnel sales activities like lead outreach, qualification, and appointment setting. It operates 24/7 to handle initial customer engagement, freeing up human sales representatives to focus on building relationships and closing deals.

Demo

Pricing & Order Agent

January 9, 2026 n28tech

Pricing Agent is a productivity tool that simplifies pricing management by reviewing and validating product pricing and pricebooks within Salesforce. It also helps with identifying and setting customer to appropriate Pricing Tier management. Order Agent is an OCR-powered productivity tool designed to streamline operations by automatically capturing and processing purchase order details into Salesforce. This agent accelerates order processing, improves data accuracy, and enhances overall operational efficiency.

Demo

Purchase Order Agent

January 9, 2026 n28tech

Purchase Order Agent is an OCR-powered productivity tool designed to streamline operations by automatically capturing and processing purchase order details into Salesforce. It extracts key fields such as quantities, pricing, and vendor information, then integrates them with relevant records to provide real-time visibility for finance, procurement, and operations teams. By reducing manual entry and errors, the agent accelerates order processing, improves data accuracy, and enhances overall operational efficiency.

Demo

Contract Agent

January 9, 2026 Samir Das

Salesforce Contract Agent is an AI-powered solution for contract management that leverages OCR to seamlessly extract key terms, dates, and obligations from uploaded contracts and automatically input them into Salesforce. The agent streamlines deal execution by configuring relevant pricing, linking agreements to customer records, and ensuring sales teams have accurate, structured contract data at their fingertips—reducing manual entry, accelerating approvals, and driving more efficient revenue operations.

AI, Salesforce CPQ, Salesforce Revenue Cloud

Part 1: From Salesforce CPQ to Revenue Cloud — What This Shift Means For Your Enterprise

September 10, 2025 Jignesh Rathod

In March 2025, Salesforce announced the End of Sale for Salesforce CPQ. For existing customers, this means you can continue to renew and maintain the product, but no new licenses, features, or innovations will be added going forward. In other words, CPQ is still running, but it’s no longer evolving. This also means migration is inevitable. In Part 1 of our Revenue Cloud Series, we’ll cover why Salesforce made this decision, what it means for current CPQ users, and how Revenue Cloud is positioned as the path forward. Why Salesforce Moved On From CPQ Acquired from SteelBrick in 2015, Salesforce CPQ was a powerful step forward at the time. But after nearly a decade, its limitations became harder to ignore for companies with complex quoting and revenue operations. The Managed Package Problem: CPQ is Not Salesforce-Native CPQ runs as a managed package on top of Salesforce, not as part of the core platform. This creates fundamental limitations: Performance bottlenecks with large product catalogs Sales reps tend to experience noticeable slowdowns when building quotes with extensive product lists, delaying response times for customers. SOQL query limits during complex quote generation Complex deals frequently hit query limits, causing timeouts mid-process, forcing reps to restart or manually split quotes. Inability to leverage Salesforce’s latest AI and automation capabilities CPQ users can’t take advantage of innovations like Einstein AI or advanced automation, leaving their sales teams behind the rest of the Salesforce ecosystem. The Innovation Drought: CPQ Doesn’t Receive Salesforce Platform Advancements CPQ hasn’t kept pace with Salesforce’s platform-wide investments in AI, automation, and modern user experiences. For example, users haven’t been able to leverage native Einstein guidance, Agentforce capabilities, or the latest Lightning improvements, leaving sales teams working in an older tool while other parts of the Salesforce ecosystem evolve. The Technical Debt Reality: Heavy Customization Creates Fragile Systems Many companies using CPQ end up with heavily customized implementations full of workarounds. Companies often find that Salesforce CPQ requires significant customization to handle edge cases or performance issues in large implementations, which can increase maintenance costs and make systems more fragile over time. The Transparency Issue: CPQ’s “Black Box” Pricing CPQ often functions as a pricing “black box,” where sales teams and customers have limited visibility into how discounts, taxes, and markups are applied. This lack of transparency can slow approvals, create confusion, and add extra steps to the quoting process. A Better Alternative to CPQ: Salesforce Revenue Cloud Revenue Cloud is Salesforce’s native, end-to-end revenue management solution, designed to unify quoting, pricing, contracts, orders, and billing in a single platform. Revenue Cloud isn’t CPQ 2.0 — it’s a fundamental rethinking of revenue management. Built natively on Salesforce’s Einstein 1 platform, it addresses every limitation of the old CPQ approach. Image Source: Trailhead Salesforce The Architecture Advantage: Built Natively on Salesforce Unlike CPQ’s managed package approach, Revenue Cloud is built directly into Salesforce’s core platform using standard objects. This means: Better performance with large datasets and complex pricing Native AI integration with Einstein and Agentforce out of the box Modern Lightning UI that feels like the rest of Salesforce API-first architecture enabling headless commerce and omnichannel experiences The Seven Pillars of Revenue Excellence: End-to-End Revenue Management Revenue Cloud Advanced is organized around seven core capabilities that cover your entire revenue lifecycle: Product/Service Design – Centralized catalog management with flexible bundling Pricing Management – Dynamic pricing with complete transparency Configure, Price, Quote – Enhanced CPQ with real-time guidance Contract Lifecycle Management – Built-in contract creation and management Order Management – Seamless order processing and fulfillment Billing – Integrated billing for all revenue models Revenue Intelligence – AI-powered insights across operations The Pricing Edge: Better Transparency with Revenue Cloud Revenue Cloud resolves CPQ’s “black box” pricing limitations by introducing pricing waterfalls that show exactly how every price is calculated—list price, discounts, taxes, markups—in real time. Sales teams and customers alike gain clarity on how a quote is built, reducing back-and-forth and accelerating deal closure. Understanding Your Revenue Cloud Options Salesforce offers Revenue Cloud in the following configurations: Revenue Cloud Growth: The comprehensive solution that replaces CPQ with Order and Asset Lifecycle Management. Revenue Cloud Advanced (RCA): The comprehensive solution that replaces CPQ, while also adding contract management, order orchestration, and basic billing capabilities. Revenue Cloud Billing (RCB): Available separately or as an add-on to RCA, this option provides advanced billing functionality such as usage-based pricing, automated collections, and revenue recognition. What This Means For Your Business If You’re Currently Using CPQ Salesforce continues to support existing CPQ customers with renewals and maintenance, but no new features or innovations will be added. To stay current with Salesforce’ AI enhancements, automation, and modern revenue management capabilities, it’s recommended to migrate to Revenue Cloud. This migration is not a simple upgrade — existing configurations, customizations, and integrations must be reimplemented and carefully configured from scratch to align with your business processes. While it requires effort, this investment is worthwhile: it replaces an obsolete system, reduces technical debt, and ensures tight integration with Salesforce’s modern platform. Planning and acting now gives your organization the time to allocate resources and execute the migration efficiently. It also ensures access to advanced AI capabilities that CPQ doesn’t provide, while minimizing disruption before outdated processes create friction. If You’re Evaluating Revenue Management Solutions Within Salesforce, Revenue Cloud is the obvious enterprise-grade choice. It not only replaces CPQ but also future-proofs your revenue operations by bringing the entire quote-to-cash cycle onto one unified platform. The Strategic Opportunity This migration from CPQ to Revenue Cloud represents a fundamental shift from point solutions to unified platforms. Companies that make this move now will have significant competitive advantages: Faster quote generation with AI-powered guidance Unified customer experience from quote to cash Better insights with integrated analytics Future-ready architecture for whatever comes next Attribute Salesforce CPQ Revenue Cloud Status End of Sale; renewals supported but no new licenses or features Actively developed with ongoing features and releases Platform Fit Managed package on top of

Penumbra & N28 Technologies Customer Story Hero Image

Customer Stories

How Penumbra Scaled Its Commercial Operations with N28’s Health and Revenue Cloud Expertise

August 20, 2025 n28tech

Customer Stories Customer Overview Company Name: Penumbra, Inc Industry: Medical Device Company Size: 5,500 employees Mission Statement: Penumbra, Inc., the world’s leading thrombectomy company, is focused on developing the most innovative technologies for challenging medical conditions such as ischemic stroke, venous thromboembolism, pulmonary embolism, and acute limb ischemia. Our broad portfolio, centers on removing blood clots from head-to-toe with speed, safety and simplicity. By pioneering these innovations, we support healthcare providers, hospitals and clinics in more than 100 countries, working to improve patient outcomes and quality of life. Key Services/Products: Neuro: Neuro Thrombectomy System, Neuro Embolization Technologies, Neuro Access Catheters, Neurosurgical Devices Vascular: Peripheral Thrombectomy Platform, Peripheral Embolization System, Vascular Access System, Coronary Mechanical Thrombectomy Website: www.penumbrainc.com/ Social Media: LinkedIn The Challenge To stay competitive in a dynamic market, Penumbra set out to strategically transform its commercial sales operations. With increasing complexity across product offerings and customer expectations, they needed to respond swiftly to market changes and continue to deliver customer value while driving cross-functional alignment. Key challenges included: Establishing a centralized view for enterprise-wide visibility: Without a centralized view of customer intelligence across sales, marketing, and operations, teams lacked the degree of visibility needed to make faster, accurate decisions. Complex workflows limiting sales productivity: Manual pricing and quoting workflows created friction—diverting sales talent away from strategic, high-value initiatives. Fragmented insights into market opportunity: Growth signals existed across systems, but without a consolidated analytics and market intelligence layer, it was challenging to proactively identify growth opportunities and expand high-potential accounts Aligning infrastructure with global scale: Existing infrastructure required improved flexibility and resilience to support Penumbra’s global expansion and future business needs. Customer Quote Why N28 Technologies? When Penumbra set out to transform its commercial infrastructure, they chose N28 Technologies for their ability to align innovation with execution, deep Salesforce expertise, and proven track record in delivering scalable, growth-ready solutions. What stood out: Strategic Execution: N28 demonstrated a strong track record of translating complex business needs into scalable, actionable Salesforce solutions. Cross-Functional Collaboration: N28 worked closely across sales, operations, and IT, ensuring the solution aligned with Penumbra’s broader commercial goals. Deep Technical Expertise: With a highly skilled team, N28 delivered a robust Salesforce implementation designed to scale with Penumbra’s evolving needs. Proactive Partnership: N28’s hands-on, collaborative approach helped accelerate delivery and maintain momentum throughout the project. The Solution To modernize and scale its commercial operations, Penumbra partnered with N28 Technologies to implement Phase 1 of a comprehensive Salesforce CRM and CPQ solution. This strategic initiative was designed to centralize customer data, optimize pricing and quoting workflows, and empower sales teams with greater visibility into key accounts—all while setting the stage for long-term growth and automation. N28 Technologies brought deep Salesforce and medtech expertise to architect a tailored solution that met Penumbra’s regulatory, operational, and commercial needs. Key features of the solution included: Customer Master in Salesforce: A unified customer master record was created to serve as a single source of truth for account data. This allowed sales, marketing, and operations teams to collaborate more effectively with shared, real-time visibility into account information. Lead and Opportunity Management: N28 implemented customized Salesforce workflows that supported Penumbra’s focus on high-value medical device accounts, including VAC (Value Account Committee) opportunities. These workflows streamlined pipeline management, improved follow-up discipline, and aligned sales activity with account-level strategy. Salesforce CPQ Integration: Penumbra’s pricing and quoting processes were transformed with Salesforce CPQ, introducing automated workflows that reduced errors, improved turnaround times, and ensured pricing accuracy across products and customer segments. System Integration: N28 ensured seamless integration with Penumbra’s existing ERP systems, including SAP, to sync customer records and pricing contracts. This alignment laid the foundation for end-to-end commercial automation and supported Penumbra’s broader goal of building intelligence-driven sales operations. Future-Ready Foundation: The solution established a flexible sales infrastructure that has positioned Penumbra to scale efficiently and respond to future market demands. Together, these components delivered a connected commercial ecosystem that not only improved present-day execution but also prepared Penumbra for future digital transformation initiatives. The Results With Phase 1 of the Salesforce CRM and CPQ implementation complete, Penumbra realized measurable improvements in operational efficiency, pricing accuracy, and commercial agility. Key results included: Faster and More Accurate Quoting: Automation through Salesforce CPQ reduced manual effort, accelerating quote turnaround time by 15-25% while improving pricing accuracy and enhancing the overall sales and customer experience. Greater Operational Alignment: Improved cross-functional alignment through centralized customer data and governance in Salesforce, with sales, marketing, legal, pricing, and operations now working cohesively within a unified system. Real-time Visibility into Sales and Marketing Performance: Enhanced visibility empowered data-driven strategies and better decision-making. Increased Agility in Responding to Market Demands: Integration of Salesforce CPQ with backend systems streamlined pricing and order management, enabling Penumbra to respond more quickly and efficiently to customer needs.

Salesforce Data Cloud, AI, Enterprise Data News, Informatica Acquisition

Salesforce Data Cloud Series Part 3: What the Informatica Acquisition Means for Enterprises That Count on Data Trust and Compliance

August 7, 2025 Jignesh Rathod

In regulated sectors like Medtech, Life Sciences, Manufacturing and IoT, innovation doesn’t begin with data—it begins with trusted data. These industries already invest heavily in ensuring data confidence, compliance, and actionable insights, all while navigating complex regulatory requirements. Salesforce’s $8 billion acquisition of Informatica becomes particularly significant within this landscape. More than just a tech merger, this move signals enhanced data governance for Salesforce, accelerating enterprise data trust and compliance across industry standard regulations like GDPR, HIPAA, and DSAR. In this final post of our Salesforce Data Cloud series, we explore what this acquisition could unlock for organizations managing complex, regulated data environments, and for the future of trusted, scalable enterprise data. In case you missed previous installments in this series, here’s Part 1: The Foundation for AI-Ready Data, where we covered the essential building blocks of Salesforce Data Cloud and Part 2: AI-Ready Data in Action, where we explored critical use cases for AI-ready data across Medtech, High-Tech & IoT, and Manufacturing. What Informatica Brings to This Acquisition: Scalable Trust and Intelligent Governance Informatica has long been recognized as a leader in enterprise-grade data management. According to Gartner’s 2024 Magic Quadrant for Data Integration Tools, Informatica was positioned as a Leader for the 19th consecutive year, ranked highest for its ability to execute and furthest for completeness of vision. Before we explore the potential significance of this acquisition, it’s worth looking at what Informatica already delivers. Known for its depth in data management, Informatica brings a mature set of capabilities that help enterprises across highly regulated industries govern, clean, and protect data at scale. Data Governance and Transparency Informatica provides tools for data cataloging, metadata management, and lineage tracking that show how data moves through the enterprise. This visibility supports audit readiness, simplifies compliance reporting, and improves oversight across increasingly complex data estates. Data Quality and Profiling With automated profiling, cleansing, and anomaly detection, Informatica ensures that data used in AI, analytics, and operations is consistent and reliable from the start. That means fewer delays, less manual cleanup, and stronger confidence in downstream decisions. Automated Privacy and Compliance Management Informatica streamlines regulatory compliance with built-in tools for data masking, anonymization, and consent tracking. It also supports DSAR (Data Subject Access Requests) compliance, required under privacy laws like GDPR and CCPA, helping teams respond quickly to individual data rights requests without tying up valuable resources. These enterprise-grade Master Data Management capabilities make Informatica a key enabler of data trust and governance in industries requiring accuracy, transparency, and compliance. Building on Salesforce’s Existing Strengths A Unified AI-Data Platform Salesforce already offers a robust suite of tools—Einstein AI, Data Cloud, MuleSoft, and Tableau—that help enterprises unify data, extract insights, and operationalize intelligence across the business. With Informatica, these capabilities are reinforced by deeper governance and quality controls that support more reliable, scalable data strategies. Data Cloud: Informatica’s Master Data Management (MDM) creates “golden records” by resolving duplicate profiles and standardizing key attributes. This enables a single, trusted view of customers and stakeholders—critical for personalization, reporting, and compliance. MuleSoft: With cleaner, governed data flowing through APIs, integrations are more dependable. This reduces failure points between systems and improves the consistency of data powering downstream workflows. Tableau: In addition to visualization, users can access metadata such as data lineage, quality scores, and compliance status. That context improves confidence in analytics and supports audit-readiness. Together, these capabilities strengthen Salesforce’s role as the backbone of enterprise data strategy—supporting more accurate reporting, faster automation, and smarter AI-driven outcomes. The Opportunity: Real-World Impact of Improved Trust & Governance The integration of Informatica’s capabilities into the Salesforce ecosystem could help enterprises build governed, high-confidence data workflows with greater scale and precision. Here’s a glimpse into what that could look like across regulated industries. MedTech & Life Sciences Clinical trials, patient records, EHR systems, and connected devices generate massive volumes of sensitive data, often trapped in disconnected systems. Informatica’s Master Data Management (MDM) creates unified “golden records” (consolidated, accurate customer or patient profiles) that resolve duplicates and enable cleaner, audit-ready datasets. Paired with Data Cloud’s real-time activation, organizations could spend 20% less time chasing orders, respond faster to care delivery needs, and automate HIPAA compliant workflows. The result: faster clinical decisions, fewer data risks, and greater patient trust. Manufacturing & IoT Siloed ERP data, supply chain systems, and production line sensors often lead to costly inefficiencies and blind spots. With Informatica’s data integration and quality layers feeding governed data into Salesforce and Einstein AI, predictive agents can proactively surface issues—whether it’s a delayed component delivery or a machinery failure. Early pilots show up to 30% efficiency gains in sales and production planning with significant cost savings from predictive maintenance powered by cleaner, more consistent data. Compliance at Scale From GDPR to HIPAA, compliance requires continuous and verifiable control over how sensitive data is accessed, processed, and stored. Informatica’s privacy tools automate consent tracking, data masking, and DSAR fulfillment, ensuring AI systems only act on data that meets privacy policies. For example, if consent is missing or inconsistent, the system can automatically pause related processes—minimizing compliance risks and reducing manual audit efforts. The combination of these platforms and strategic implementation could empower enterprises to move beyond data firefighting towards faster, more confident decisions on trusted, compliant data. CLAIRE + Agentforce: Context-Aware AI That Operates With Confidence Informatica’s CLAIRE engine brings deep, metadata-driven intelligence to enterprise data. When combined with Salesforce’s Agentforce platform, it powers a new generation of AI agents—ones that don’t just access data, but understand the context, rules, and relationships that govern it. Imagine asking, “Why is revenue different in Salesforce vs. Tableau?” Instead of raising a ticket for manual investigation, an AI agent powered by Claire GPT could trace the data lineage, flag the inconsistency, and suggest next steps with complete transparency. Or consider an AI agent detecting an anomaly in an IoT device, checking regulatory impact, verifying service policies, scheduling a technician, and notifying the customer. Every action is logged to meet compliance requirements, and decisions

Salesforce Data Cloud, AI, Blog, Enterprise Data Management

Salesforce Data Cloud Series Part 2: AI-Ready Data in Action

June 25, 2025 Jignesh Rathod

No matter how advanced your AI models get, the true power of enterprise AI boils down to the quality and structure of data that fuels it. Without a clean, unified foundation, even the most ambitious AI strategies can fall short, leading to fragmented insights, unreliable automation, and limited scalability. In our previous post, Salesforce Data Cloud Series Part 1 — The Foundation for AI-Ready Data, we covered the various steps your enterprise data takes to become AI-ready—from ingestion and harmonization to identity resolution and real-time activation. But, what can this AI-ready data unlock for your enterprise? In Part 2 of this 3-part series, we move from architecture to impact—highlighting real-world use cases of Salesforce Data Cloud’s AI capabilities across Medtech, Manufacturing, High-Tech and IoT. Figure 1: Unified, comprehensive customer profiles are a core outcome of Salesforce Data Cloud’s Identity Resolution step, post data ingestion and harmonization. (Source: Salesforce.com) AI-Ready Data in MedTech – Enhancing Patient Outcomes and Device Management The Challenge In MedTech, enterprise data is everywhere—scattered across clinical trials, patient records, and connected devices. Without a unified view, your teams lack real-time insights, and are often left waiting or relying on guesswork to answer critical questions like: “How are our devices performing in the field?”, “Are we pricing effectively?”, “How can we accelerate deal cycles?”, and “Where are our biggest compliance gaps?” This data fragmentation undermines efforts to drive patient outcomes, operational efficiency, and regulatory compliance. Gaining a clean, unified view of your data is essential to ensure better device performance and tangible business impact. How Salesforce Data Cloud Unifies MedTech Data to Power Enterprise Outcomes Salesforce Data Cloud transforms MedTech’s fragmented data into actionable insights in real-time by: Ingesting data from clinical trials, patient records, and connected devices into a unified platform. Standardizing and cleaning data to resolve inconsistencies across systems. Resolving patient identities across scattered sources to create accurate, consolidated patient profiles. Segmenting data by geography, usage trends, provider, or clinical pathways to enable targeted actions. Leveraging AI models to identify patterns in device usage and patient response—helping teams anticipate maintenance, spot at-risk patients, and support care proactively. In practice, this means your teams have consistent, unified access to real-time insights that enable proactive device management and patient outcomes. What Enterprise Outcomes Can AI-Ready Data Drive for MedTech? AI-ready data delivers tangible, enterprise-level benefits, including: Better patient outcomes with personalized care and proactive device management that cut downtime and boost treatment effectiveness. Greater operational efficiency through automated insights, streamlined pricing, and reduced manual work and errors. Stronger regulatory confidence with accurate, harmonized data, full audit trails, and real-time quality monitoring. For example, fragmented data can cause MedTech teams to spend up to 20% of their time on administrative tasks like order tracking. By integrating disparate systems and leveraging AI-ready data, MedTech organizations can significantly reduce these inefficiencies—cutting operating costs by up to 30% and enabling teams to focus on strategic priorities. AI-ready data is critical for MedTech companies aiming to simplify operations, improve patient outcomes, and drive growth, while remaining compliant. Wondering what AI-ready data can do for your MedTech enterprise? Get in touch to explore our offerings. AI-Ready Data in Manufacturing – Maximizing Operational Efficiency and Forecast Accuracy The Challenge In manufacturing, enterprise data is scattered across ERP systems, production lines, inventory, and quality control. Without a unified view, your teams lack real-time visibility and are often forced to rely on manual workarounds or incomplete data to answer questions like: “Where are we running short or overproducing?”, “Are we catching downtime risks before they escalate?”, and “How reliable is our forecast?” This data fragmentation undermines your efforts to prevent downtime, optimize planning, and maintain consistent production quality. Gaining a clean, unified view of your data is essential to streamline operations, improve forecast accuracy, and deliver tangible business impact. How Salesforce Data Cloud Unifies Manufacturing Data to make it AI-Ready Salesforce Data Cloud transforms manufacturing’s fragmented data into actionable insights in real time by: Ingesting data from ERP systems, production lines, and quality control into a centralized platform—giving operations teams a single source of truth. Segregating data by manufacturing unit or region to allow local teams control while ensuring centralized visibility and governance. Powering real-time dashboards and automating alerts for inventory shortages or production anomalies—so teams can respond faster and more effectively. Leveraging advanced forecasting models to predict equipment failures and demand fluctuations—helping teams minimize downtime and optimize resource planning. In practice, this means your teams have consistent, unified access to real-time insights that keep production efficient, planning accurate, and operations resilient. What Enterprise Outcomes Can AI-Ready Data Drive for Manufacturing? AI-ready data delivers tangible, enterprise-level benefits, including: Greater operational efficiency through real-time visibility and automated alerts that reduce downtime and keep production flowing. Lower costs from proactive maintenance and accurate forecasting that minimize production waste and expensive equipment failures. Improved customer experience through reliable supply chains and production schedules that support consistent delivery. For example, fragmented data can cause inefficiencies in sales planning and forecasting—limiting visibility and delaying decision-making. By integrating disconnected systems and leveraging AI-ready data, manufacturing organizations can boost sales planning efficiency by up to 30% and improve forecast accuracy across the board. AI-ready data is essential for manufacturers looking to reduce downtime, lower costs through proactive maintenance, and improve forecast accuracy and customer experience. Wondering what AI-ready data can do for your Manufacturing enterprise? Get in touch to explore our offerings. AI-Ready Data in High-Tech & IoT – Driving Real-Time Insights and Scalable Innovation The Challenge In High-Tech and IoT, enterprise data flows in from everywhere—devices, sensors, apps, and user interactions—often scattered across disconnected systems. Without a unified view, your teams lack real-time visibility and are left relying on fragmented signals to answer key questions like: “Which features are actually being used—and which aren’t?”, “Where and when are our devices at risk of failure?”, “How can we tailor support based on individual user behavior?” This data fragmentation slows innovation, limits personalization, and makes it harder for your teams to respond to users