Skip to content

Read an exclusive report on the combined impact of US Tariff and China Procurement Reforms for MedTech and Life Sciences industry

N28tech-Logo
  • What We Do
    • Agentforce Accelerators
  • About Us
  • Careers
  • Resources
    • Blog
    • Customer Stories
    • AI Agents
    • Case studies
Contact Us

Agentforce

  • Home
  • Agentforce
Salesforce Channel Revenue Management
Agentforce, AI, AI Agents, Blog, Salesforce Revenue Cloud

Salesforce Channel Revenue Management: What It Does, How It Stacks Up, and Who It’s Actually For

June 25, 2026 Nithya Konduru

Channel revenue is one of the messiest problems in B2B. Distributors, wholesalers, and resellers move your product, but the data they send back is inconsistent, the rebate claims pile up, and by the time finance reconciles everything, someone has already been overpaid. For companies that have already built their commercial operations on Salesforce, the platform’s Channel Revenue Management product offers a way to bring order to that chaos without standing up an entirely separate system. But “Salesforce can do that too” isn’t the same as “Salesforce does it best.” Here, we explore what Salesforce Channel Revenue Management actually covers, where it has real advantages, and how it compares to the other tools companies typically evaluate when this problem gets serious enough to budget for. What Salesforce Channel Revenue Management Is Built to Do The product is designed to help businesses manage and optimize financial incentives, rebates, and pricing strategies while improving collaboration with channel partners through visibility into sales performance, inventory tracking, and incentive programs. In practice, that means a few distinct capabilities working together.  The platform lets you automate important partner processes like deal or design registrations and claim requests, and brings rebate claim requests,  point-of-sale transactions, and channel partner transaction histories into your CRM. Partners can see new rebate opportunities, claim status, and payout information directly through their partner experience without needing to call anyone. On the rebate side specifically, program managers can define incentive rules to ensure accurate payout calculations based on growth, unit, amount, or custom measurements. The product includes tools for managing partner rebates from growth-based programs to ship and debit or price protection models, helping ensure that partners are paid correctly and on time while protecting the bottom line.  What makes this different from a standalone rebate tool is that it is native to Salesforce. There is no separate system to stand up, no middleware to manage, and no integration project to fund. Channel Revenue Management sits on the same data model and the same UI as Sales Cloud, Manufacturing Cloud, and every other part of the Salesforce platform your team already uses. For organizations already running on Salesforce, that alone removes a significant layer of cost and complexity that comes with channel-specific point solutions. The Agentforce Addition The Summer 2026 release cycle has brought meaningful AI additions to the product. Agentforce for Channel Revenue Management simplifies the management of rebate programs and payout processes through natural language interactions. With predefined agent topics and actions, teams can track calculations, resolve issues with payout insights, and review overall rebate program details to ensure transparency, traceability, and accurate claims.  The broader Revenue Management roadmap has focused on a “less clicking, more selling” theme, with the Summer ’26 updates aimed at reducing friction in quoting and approval workflows. For channel operations teams managing large numbers of rebate lines, the ability to query and resolve payout issues through a conversational interface is a genuine time saver.  How It Compares to Model N Model N is the comparison that comes up most often for channel-intensive industries, and it deserves a direct look. Model N has built its reputation over 25 years primarily in pharmaceutical and life sciences, where regulatory compliance requirements are genuinely complex. Government pricing, including Medicaid, 340B, and VA programmes, export compliance, and global tender management in those sectors involve specialised rules that Model N has spent decades encoding into its platform. For a large pharma company with operations across 50+ countries and hard compliance obligations, that depth is real. Outside pharma and life sciences, however, the picture changes considerably. For manufacturing and semiconductor companies, Salesforce Channel Revenue Management covers the vast majority of what channel operations teams actually need, including rebate management, inventory tracking, deal registration, and partner visibility, and does so natively within a platform they already own. The case for displacing that with a separate Model N implementation, which typically runs 12 to 18 months and relies heavily on the vendor’s own professional services team, is hard to make. It is also worth noting that Model N’s AI story remains largely on the roadmap. Their “Autonomous Revenue Science” positioning, covering AI contract drafting and machine learning fraud detection, is directional rather than broadly available today. Agentforce, by contrast, is shipping now. For most manufacturing and hi-tech companies outside heavily regulated life sciences, Salesforce is not just a credible alternative to Model N. It is the stronger operational choice. How It Compares to SAP and ERP-Native Approaches Some organizations default to managing channel incentives inside their ERP, typically SAP S/4HANA or similar. SAP S/4HANA Cloud handles order management encompassing the quote-to-cash workflow, including order placement, fulfillment, invoicing, and revenue recognition, and integrates with financial accounting systems to facilitate revenue reporting and decision-making.  The problem with this approach is visibility. When rebate program data lives inside the ERP, sales teams and partner managers typically can’t access it easily. Finance owns the numbers, RevOps owns the strategy, and partners have no self-service at all. In many organizations, incentive program management and information is siloed both by department and by tool, with programmes often managed by finance teams who rely on point solutions, spreadsheets, or an ERP that is not accessible to account managers or channel partners.  Salesforce Channel Revenue Management addresses this by bringing that data into the CRM where the people who run partner relationships can actually use it. The ERP integration still exists for financial reconciliation, but day-to-day operations move off spreadsheets and into a system that sales and channel ops teams already live in. The Partner Ecosystem Factor One dimension that often gets overlooked in product comparisons is the implementation ecosystem. Model N’s delivery model is relatively closed, with the vendor’s own professional services team playing a central role in most projects. Salesforce operates on an open SI partner model, with a large global network of implementation partners who know the product well. Salesforce provides a predefined Manufacturing Experience Cloud template to accelerate the partner portal setup, and the Experience Cloud integration enables

Blog, Agentforce, AI, Salesforce Health Cloud, Salesforce Life Sciences Cloud

From Paperwork to Patient Care: Solving the Home Health Capacity Crisis with Salesforce

January 29, 2026 Samir Das

In today’s healthcare landscape, the home has become the new frontline. Patients are increasingly choosing to age in place, and post-acute recovery is shifting from hospital wards to living rooms. For home health providers, this transition represents opportunity but it has also exposed a growing capacity crisis. Referral volumes are rising, payer rules are tightening, and staffing shortages persist. Yet many agencies are still operating with legacy systems, spreadsheets, and manual handoffs that were never designed for this level of operational complexity. The result is delayed starts of care, burned-out staff, preventable denials, and limited visibility into where the business is actually constrained. At N28 Technologies, we see these challenges firsthand. As a Salesforce partner specializing in healthcare operations and AI-driven alignment, we believe the solution isn’t simply adding more tools but building a unified operational platform that allows teams to focus on patients, not paperwork. The Invisible Hurdles Holding Home Health Back Before discussing technology, it’s important to be clear about the realities facing home health agencies in 2026. Documentation Fatigue and Revenue Leakage Clinicians often spend nearly a third of their day on administrative tasks. When documentation is manual, duplicated, or disconnected from intake and payer data, it doesn’t just lead to burnout—it creates downstream issues like claim rework, delayed billing, and avoidable denials. Over time, this administrative drag directly limits how many patients an agency can safely serve. Fragile Scheduling at Scale In home health, one caregiver call-out, traffic delay, or rescheduled visit can trigger a domino effect across an entire day’s route. Authorizations, visit frequency compliance, and patient satisfaction all take a hit. Yet many agencies still manage scheduling with static spreadsheets that offer no real-time visibility or ability to dynamically re-optimize. Data Silos That Undermine Value-Based Care Patient vitals, therapy notes, insurance eligibility, authorizations, and family communications often live in separate systems. This fragmentation makes it extremely difficult to manage value-based care contracts, where outcomes, utilization, and documentation quality are tightly linked. Leadership teams are left making decisions without a complete, trusted picture. A Real-World Example: What This Looks Like in Practice To make this concrete, consider a large home health provider we recently worked with serving tens of thousands of patients annually and experiencing rapid referral growth. Despite strong demand, the organization was facing: Intake backlogs driven by manual insurance verification Delays in start of care due to authorization visibility gaps Limited insight into where referrals were stalling High operational strain on intake and field teams The agency implemented Salesforce as an operational layer integrated with their payer systems to modernize intake and field operations. Key outcomes: 30 – 40% reduction in referral-to-start-of-care cycle time Improved authorization visibility across intake, scheduling, and billing Leadership gained dashboards showing referral-to-Start of Care (SOC) timelines and bottlenecks by payer and region Growth came from removing friction and not by adding headcount. The Salesforce “House Call”: A Modern Operating Platform for Home Health Salesforce has evolved far beyond a traditional CRM. For home health agencies, it now serves as an operational layer that connects intake, field operations, payer workflows, analytics, and AI. Salesforce Health Cloud: A True 360-Degree Patient View Health Cloud replaces fragmented records with a unified patient profile. Intake teams can see referral details, insurance information, prior visits, social determinants of health, and authorization status in a single view, without toggling between systems. When integrated with an EHR, Health Cloud becomes the system of orchestration rather than duplication. Recurring visits, electronic visit verification (EVV), and care plans are embedded directly into workflows, making compliance a byproduct of daily operations rather than an after-the-fact exercise. Salesforce Field Service: Intelligent Logistics for Mobile Care Field Service acts as the operational brain for the home health workforce. Intelligent Scheduling: Automatically matches clinicians to patients based on skills, proximity, availability, and visit requirements Faster Start of Care: Shortens referral-to-SOC timelines, one of the most critical drivers of both growth and patient satisfaction Mobile Productivity: Clinicians work from a mobile app that functions offline, captures signatures at the door, and syncs documentation back to the office in real time The result is fewer missed visits, higher clinician utilization, and better patient experiences. Agentforce: AI That Reduces Friction, Not Trust The most significant shift we’re seeing in 2026 is the rise of autonomous AI agents through Salesforce Agentforce. Unlike traditional AI “assistants,” these agents can take action within guardrails: Self-Scheduling Support: When a caregiver calls out, an AI agent can suggest rerouting options, flag authorization impacts, and notify patients of updated arrival windows Clinical & Intake Summarization: AI can synthesize lengthy referral packets into concise pre-visit briefs, allowing clinicians and intake teams to walk in fully informed The goal isn’t to replace staff but to eliminate decision fatigue and administrative drag so teams can focus on judgment-based, patient-centric work. Improving the Patient and Family Experience Operational efficiency is only half the equation. The other half is trust. Using Salesforce Experience Cloud, agencies can offer secure portals where patients and families can: View upcoming visits Message the care team Access educational materials and care updates This transparency reduces inbound “status check” calls and helps families become active partners in care which data shows consistently improves patient satisfaction. Over 50% of patients surveyed indicated a preference for online portals by providers. Final Thought The agencies that succeed in the next decade of home health won’t do so by adding more staff or more spreadsheets. They’ll win by building smarter, more resilient operations. Salesforce provides the foundation. AI (within guardrails) multiplies the impact. If your organization is evaluating Salesforce for patient intake, insurance verification, or AI-enabled operations, we’re happy to share what’s working in the field and what to avoid. Contact us today for a free assessment and discover how we can help you transform operations for the modern era.

AI-powered Salesforce Admin Assistant Blog Post Header Image
AI, Agentforce

Will Agentic Experience Replace Salesforce Admin App?

May 13, 2025 Ajay Achuthan

Still navigating the maze of Salesforce Admin menus? Click after click, it goes on and on— just to check a user’s permissions or debug an error buried in classic UI. Not anymore, thanks to our AI-powered Salesforce Admin Assistant. Admin tasks shouldn’t feel like an obstacle course. As AI transforms every corner of business operations, why are admins still stuck in a manual, outdated workflow? The future isn’t another clunky dashboard, it’s an interactive AI-powered agent that automates tasks, simplifies troubleshooting, and makes administration effortless. It’s time to rethink how we manage enterprise platforms.  This curiosity started a journey for us. First stop: Has anyone asked these same questions, and what have they done so far? After exploring a few companies and their offerings in this space, one thing became clear: While AI-powered admin solutions exist, they often fall short in critical areas. They either lack the depth to truly automate complex workflows, or they compromise on security and compliance—two non-negotiables for any enterprise. With years of managed services expertise, we saw an opportunity to craft something different: An AI-driven admin experience that doesn’t just execute tasks, but does so with enterprise-grade security, full auditability, and compliance embedded at every step. The goal isn’t just to replace manual clicks, it’s to redefine what administration should look like in an AI-first world. We foresee a major shift toward AI agents handling up to 80% of Salesforce admin work, freeing up human teams to focus on high-value strategic initiatives. So, what exactly falls under this 80%? After years in the Managed Services business, we’ve built a precise catalog of admin functionalities that Salesforce operations teams rely on daily.  These include: User Management: Provisioning, deprovisioning, and managing permissions with full compliance tracking. Data Management:  Automated deduplication, data enrichment, and cleanup tasks to keep CRM data pristine. Security & Compliance: Proactive monitoring, audit logging, and anomaly detection to prevent misconfigurations. Automation & Workflow Optimization: Intelligent process automation to reduce manual interventions and inefficiencies. Issue Resolution & Debugging: AI-driven troubleshooting to diagnose errors and recommend fixes instantly. The journey from idea to execution was intense. After three months of relentless coding, testing, and refining, we soft-launched the beta version of Admin Assistant, equipped with a subset of critical functionalities designed for select clients and built to handle the most time-consuming Salesforce admin tasks with speed, security, and precision. Here is a quick preview: https://youtu.be/0p6dDYiyHMg So, what have we learned so far? Business Sense: Every client we’ve introduced this to goes absolutely bananas over how it takes their admin game to the next level. Two things are clear: 1. Those mind-numbing admin tasks they’ve been drowning in? Gone. They couldn’t hit “delete” fast enough, and 2. No more digging through Google or wading through Trailheads for answers to the tough stuff. They just chat, get it done, and move on. This level of excitement? It’s been a game changer for us. Technical Sense: Security and compliance? Front and center in our design thinking. While some of the alternatives out there take the risky route of executing Salesforce APIs with its data from an external data center, we purposely went all-in on a fully Salesforce-native design. Our solution is built 100% on Salesforce, leveraging the full power of AgentForce. No shortcuts, just raw, unfiltered security and performance. What’s Next from our AI-powered Salesforce Admin Assistant? With these early wins, we’re doubling down. Expanding Functionality: Our goal is to cover 100% of critical admin workflows, ensuring teams can operate with near-zero manual effort. Deepening Security & Compliance: Built 100% on Salesforce native architecture, we’re eliminating external API risks while integrating auditability and governance at every level. User Experience at the Core: We’re refining the AI’s conversational capabilities to make interacting with Salesforce as seamless as texting a colleague—no more endless clicking, searching, or troubleshooting. Our Admin Assistant app is designed to complement Salesforce’s new “Agent for Setup.” While Agent for Setup is an AI-powered tool that helps admins navigate, configure, and manage Salesforce more efficiently using natural language, offering quick access to tasks like managing permissions and creating report types, N28’s Admin Assistant goes further. It supports more complex administrative workflows such as report rationalization, permission set optimization, metadata cleanup, and advanced configuration management, enabling admins to drive greater efficiency, governance, and scalability within their Salesforce environments. The days of navigating clunky admin interfaces are numbered. The future? A fully AI-powered, self-optimizing Salesforce environment. And we’re just getting started. Get In Touch

get started on Agentforce
Agentforce, AI

How Should You Get Started on Agentforce

February 24, 2025 Ajay Achuthan

Most people we talk to share a common challenge: they recognize the potential benefits of Agentforce and are eager to explore but are uncertain about how to proceed. Many struggle to bridge the gap between Salesforce’s AI vision and the tangible value it can deliver to their organization. These conversations often highlight recurring themes: determining the most effective Agentforce use case for the business, assessing the effort required to bring it to market, and understanding the financial implications. Effective Agentforce use cases Different types of agents available with Agentforce. Salesforce’s Agentforce offers businesses customizable AI agents that automate routine tasks such as order tracking, customer support, and troubleshooting. These agents integrate seamlessly into various communication channels, improving operational efficiency and delivering personalized service. As AI handles simple tasks, it frees human agents to tackle more complex issues. The platform also uses AI for knowledge assistance and can escalate complicated queries to human agents when necessary, ensuring that businesses can provide the right support to their customers. For more details, check out Salesforce’s Agentforce Use Cases. At N28, we have successfully assisted clients in a variety of impactful use cases to get started on Agentforce. Here are some examples: Sales and marketing use cases Generate quotes: Where our AI agents interact with Sales staff to produce customized quote PDF documents for specific customers. AI Account manager: Recommend products based on insights from current orders and market data, optimizing sales strategies. Operational use cases Validate purchase orders: Automating tasks like price checks, identifying complex offer pricing, and initiating rebate calculations Admin AI: Automates routine administrative tasks within Salesforce orgs, saving time and reducing manual effort. Technical framework behind Agentforce Agentforce’s architecture is built on four fundamental components that work in harmony to deliver intelligent, secure, and effective agent-based solutions: Data for AI: Foundation begins with comprehensive data integration capabilities, supporting both structured and unstructured data from internal and external sources. This robust knowledge base serves as the fundamental building block that powers agents’ decision-making and operational capabilities.  Large Language Models (LLMs): Leverages state-of-the-art LLMs to transform raw data and analytics into natural, conversational interactions. This technology enables fluid communication between users and agents, making complex data accessible and actionable through intuitive dialogue. Agent Core: A sophisticated suite of tools for designing customized agent experiences. This framework enables organizations to: Define Topics: Create precise agent parameters through detailed instructions, descriptions, and clearly defined operational scope Configure Actions: Establish specific, executable tasks and operations within each defined topic area Trust framework: A comprehensive security and governance layer that ensures controlled access management, secure channel operations, compliant agent interactions and protected data handling. This integrated architecture ensures that Agentforce delivers not just powerful AI capabilities, but does so within a secure, controlled, and trustworthy environment. Other common questions Data Cloud: Agentforce leverages the power of Data Cloud while maintaining implementation simplicity. While Data Cloud activation is a prerequisite for Agentforce deployment, organizations can begin operations using solely their CRM data—eliminating the need for extensive Data Cloud configuration at launch. Key architecture points: Data Cloud houses the Vector Database infrastructure required for RAG (Retrieval Augmented Generation) implementations Initial deployment can operate efficiently with existing CRM data Flexible architecture allows for gradual expansion of Data Cloud functionality This approach enables rapid deployment while preserving the option for enhanced Data Cloud integration as organizational needs evolve. LLM options: Out-of-box support: Pre-configured integration with select OpenAI models Pre-configured integration with select Anthropic models Flexible deployment: Support for custom LLM integration (“bring your own model”) Maintain control over your preferred large language models This flexible architecture allows organizations to leverage either pre-integrated models or implement their preferred LLM solutions based on specific requirements. Financial overview License cost: Unlike traditional user licensing, Agentforce employs a conversation-based pricing structure, charging $2 per agent interaction, with potential volume discounts. This model shifts costs from upfront licensing to usage-based fees, potentially reducing initial expenses but increasing costs with higher usage. There might be additional costs associated with Data Cloud credit usages and LLM model usages. With this on-demand pricing model, organizations must evaluate the trade-off between automating tasks through Agentforce and the associated per-interaction fees to determine the most cost-effective approach. N28 implementation cost: Staged implementation approach. Understanding that AI adoption requires careful consideration, we’ve designed our AI services to support a measured, step-by-step implementation journey. Click the link below to review our Agentforce offerings. Check Out Our Agentforce Offerings Here.

Why Smart Companies Are Doubling down on Salesforce AgentForce
Agentforce, AI

Why Smart Companies Are Doubling down on Salesforce Agentforce

January 22, 2025 Ajay Achuthan

Dreamforce ’24 was an outstanding event for Salesforce AgentForce. I gained valuable insights into Salesforce strategy, engaged in productive client meetings, and, most importantly, had meaningful conversations with peers about what customers are seeking in Data Cloud and Gen AI. For large companies with established data engineering capabilities and existing investments in business intelligence, what’s the value in further investing in Data Cloud and AgentForce? And for smaller companies, is AgentForce truly affordable? So, what is Agentforce? Salesforce’s solution empowers clients to build autonomous agents on top of their existing Salesforce platforms. It goes beyond traditional bots with integrated GenAI capabilities and surpasses standard data warehouses by grounding responses in real-time data. The standout feature is the intelligent learning engine, Atlas, which identifies the next-best action based on ongoing interactions. For me, the best part of AgentForce is its no-code/low-code functionality, enabling faster use-case deployment and significantly reducing time-to-market. Here is a summary of all the components that make up AgentForce: Why would Agentforce need Data Cloud? Data Cloud, on the other hand, serves as a microcosm of broader business intelligence capabilities—typically offered by comprehensive platforms like Snowflake or Databricks—integrated directly within the Salesforce ecosystem. It provides out-of-the-box extract, transform, and load (ETL) capabilities for data residing both within and outside of Salesforce organizations, laying the groundwork for advanced in-platform analytics. The platform’s zero-copy capabilities address the persistent data duplication challenge, ensuring data integrity and security. AgentForce relies on Data Cloud to deliver transformed business insights, enhancing response accuracy and relevance by incorporating contextually relevant information, regardless of data location. Here is a top-down view of how it works: Should larger companies adopt Agentforce? Absolutely—and for a straightforward reason: speed to market. For companies that prioritize building from the ground up and have substantial engineering resources, creating a fully customized AI capability in-house is achievable and may lead to standout, GenAI-driven innovations—you might be the next technology product unicorn start-up on Gen AI. However, for most companies where rapid market deployment is essential to maintain a high standard of user experience for both internal and external users, AgentForce offers a streamlined path to implementing GenAI use cases on the business front lines. This empowers agents to enhance sales and service team support with minimal lead time. Should smaller companies venture into Agentforce? Unequivocally, yes. With 45% of the U.S. population already using Generative AI, these capabilities are becoming a necessity. It’s only a matter of time before customers and employees demand GenAI features in every platform they interact with. While building in-house GenAI expertise and infrastructure can be costly—not to mention the ongoing operational expenses—AgentForce offers a compelling solution. Its on-demand pricing model, combined with a no-code/low-code platform, significantly mitigates investment risks, while the faster time-to-market makes it an obvious choice for smaller companies. What should the roadmap for Agentforce look like? This is not an easy question to answer, but there are several clear and established approaches for enabling the organic adoption of this new technology. To begin with, GenAI use cases focused on workflow automation represent the low-hanging fruit—such as automating customer interactions for service requests or automating lead qualification, for example. Future phases should concentrate on creating entirely new workflows driven by GenAI: replacing manual, time-consuming processes (like navigating through countless clicks) with more efficient, streamlined solutions. Additionally, developing next-best-action use cases will be key in maximizing the potential of GenAI. What is more important than all the tech talk is to STOP procrastinating. N28 is here to help. Use the form below to get in touch regarding your next project. Get In Touch

Search

Recent posts

  • Salesforce Channel Revenue Management
    Salesforce Channel Revenue Management: What It Does, How It Stacks Up, and Who It’s Actually For
  • Three corporate workers on a laptop
    Salesforce CPQ End-of-Sale: What RevOps Teams Need to Do Now
  • Three people looking at a sceen
    Why Most MedTech AI Pilots Never Reach Production
Footer white Logo
  • What We Do
  • About Us
  • Contact Us
  • Blog
  • Customer Stories
  • Privacy Policy