What Manufacturers Should Look for in a Modern ERP Platform

Manufacturers are facing growing pressure to improve efficiency, increase visibility, and support growth without adding complexity. As labor constraints, rising costs, and supply chain challenges continue, many organizations are rethinking whether their current systems can support the business moving forward.

In this Nucleus Research report, explore the trends shaping the ERP market and learn what manufacturers should consider when evaluating solutions to support operational performance, automation, and future growth.

You'll learn:

  • How manufacturers are using ERP to improve operational visibility and coordination
  • Why automation, AI, and usability are becoming key evaluation criteria
  • What capabilities help organizations scale without increasing complexity
  • Which ERP vendors are recognized as market leaders

Whether you're planning a modernization initiative or simply exploring what's changing in the ERP landscape, this report provides valuable insight into what leading manufacturers are looking for in today's ERP platforms.

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How Manufacturing ERP Solutions Compare in 2026

Manufacturers evaluating ERP solutions face no shortage of options. As operations become more complex and the need for visibility, automation, and agility grows, choosing the right platform has never been more important.

In this G2 Grid® Report, explore how leading mixed mode ERP solutions compare based on customer satisfaction, market presence, and feedback from real users. The report highlights the platforms manufacturers rely on to support production, supply chain, inventory, quality, and business operations.

You'll learn:

  • Which ERP solutions are recognized as leaders in the market
  • How real users rate leading mixed mode ERP platforms
  • Key capabilities manufacturers should consider during ERP evaluations
  • How top solutions support complex manufacturing environments

Whether you're actively evaluating ERP systems or planning for future modernization, this report provides valuable insights to help guide your research.

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How to Deploy AI on the Shop Floor—and Scale with Confidence

Manufacturers are under increasing pressure to do more with less. Labor shortages, production complexity, supply chain disruption, and rising customer expectations are pushing organizations to explore AI—but success depends on turning operational data into faster, more informed decisions.

In this IDC PeerScape report, discover how manufacturers are using agentic AI to connect people, machines, and data in practical ways that improve productivity, decision-making, and operational resilience.

You’ll learn how to:

  • Turn disconnected data into real-time insights and actions
  • Help frontline teams make faster, more informed decisions
  • Improve production, scheduling, and resource utilization
  • Automate quality and operational workflows

Whether you're just beginning to explore AI or looking to expand existing initiatives, this report offers practical examples and guidance from manufacturers already putting these technologies to work.

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State of Context Management Report 2026

DataHub commissioned independent research firm TrendCandy to survey 250 IT and data leaders about the state of context management in 2026. The findings reveal a market at an inflection point: high confidence, real infrastructure gaps, and a correction already underway.

What you'll learn:

  • Why organizations that self-assess at the highest stage of context management maturity still struggle with the fundamentals
  • How “good enough” context solutions that work in pilots consistently break down at production scale
  • Why 83% of IT and data leaders now believe agentic AI cannot reach production value without a dedicated context platform
  • What the surge in context management infrastructure investment reveals about where the market is heading
  • The three imperatives for data and IT leaders in 2026
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Unlocking AI’s Potential Through Context Management

Context engineering was supposed to solve AI’s scalability challenges. Teams are building RAG pipelines, crafting prompt templates, and implementing memory systems—each application starting from scratch. As AI scales organization-wide, these tactical approaches hit fundamental limits: fragmented systems, inconsistent outputs, and no organizational context intelligence.

This keynote explores the essential building blocks of an enterprise context platform and introduces context management as the emerging discipline that changes how organizations approach this challenge.

Key Takeaways:

  • Understand the fundamental differences between metadata for humans and context for AI agents
  • Learn why current context engineering approaches create compounding technical debt that kills enterprise AI scaling
  • Discover the emerging architectural pattern that transforms context from bottleneck to competitive advantage
  • Explore the transformative possibilities that context management will unlock for enterprise AI
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State of Context Management Report 2026

DataHub commissioned independent research firm TrendCandy to survey 250 IT and data leaders about the state of context management in 2026. The findings reveal a market at an inflection point: high confidence, real infrastructure gaps, and a correction already underway.

What you'll learn:

  • Why organizations that self-assess at the highest stage of context management maturity still struggle with the fundamentals
  • How “good enough” context solutions that work in pilots consistently break down at production scale
  • Why 83% of IT and data leaders now believe agentic AI cannot reach production value without a dedicated context platform
  • What the surge in context management infrastructure investment reveals about where the market is heading
  • The three imperatives for data and IT leaders in 2026
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Unlocking AI’s Potential Through Context Management

Context engineering was supposed to solve AI’s scalability challenges. Teams are building RAG pipelines, crafting prompt templates, and implementing memory systems—each application starting from scratch. As AI scales organization-wide, these tactical approaches hit fundamental limits: fragmented systems, inconsistent outputs, and no organizational context intelligence.

This keynote explores the essential building blocks of an enterprise context platform and introduces context management as the emerging discipline that changes how organizations approach this challenge.

Key Takeaways:

  • Understand the fundamental differences between metadata for humans and context for AI agents
  • Learn why current context engineering approaches create compounding technical debt that kills enterprise AI scaling
  • Discover the emerging architectural pattern that transforms context from bottleneck to competitive advantage
  • Explore the transformative possibilities that context management will unlock for enterprise AI
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How Highmark Federal Credit Union Automates 40+ File Transfers And Detects Fraud With MOVEit

Highmark Federal Credit Union started as a teacher's credit union in a broom closet under a stairwell. Today, it serves members across five locations in two states and depends on MOVEit Automation to keep critical file workflows running around the clock.

What you'll learn:

  • How Highmark automated 30 to 40 recurring tasks including ACH payroll processing, eStatement delivery, and daily banking notices
  • How they built a custom fraud detection program that uses MOVEit to flag suspicious transactions and generate daily call lists for their team
  • Why their strategy treats automation as a force multiplier for staff, not a replacement, freeing programmers and analysts to focus on projects that move the business forward
  • How MOVEit has delivered three years of uptime with zero outages across their Progress tech stack including WS_FTP Pro and ShareFile
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How IT Teams Build Resilient File Transfer Operations

One misconfigured backup. One untested restore. That's all it takes to turn a routine outage into a full-blown crisis for your file transfer workflows.

In this on-demand webinar, Jim Cashman, Product Manager for MOVEit Automation and a veteran IT director, shares a step-by-step maturity model for protecting the file movements your business depends on - from financial transactions and medical billing to insurance claims and partner data exchanges.

What you'll learn:

  • How to set RTO and RPO targets that align with your business requirements and compliance obligations
  • A practical backup strategy using the 3-2-1 rule - and how to test restores without accidentally running production tasks
  • How to set up a standby server for manual disaster recovery so you can restore service in minutes
  • When automated failover makes sense and how MOVEit Failover keeps two servers synced in near real time
  • A staging and testing methodology used by the most mature file transfer operations
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Turn Healthcare Data Into Actionable Insights Securely and at Scale

Healthcare organizations sit on enormous volumes of clinical data spread across disconnected systems. Without the right architecture, that data stays siloed - slowing decisions, creating compliance risk and limiting patient outcomes.

In this article, you will learn:

  • How modern healthcare data pipelines move from paper records to unified digital ecosystems
  • Why ETL processes are critical for clinical data quality and consistency
  • How AI enables real-time processing, predictive analytics and smarter clinical decisions
  • What it takes to build HIPAA-compliant pipelines that balance accessibility with security

Read the full article for a practical look at how AI is reshaping healthcare data infrastructure from the ground up.

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Turn Healthcare Data Into Actionable Insights Securely and at Scale

Healthcare organizations sit on enormous volumes of clinical data spread across disconnected systems. Without the right architecture, that data stays siloed - slowing decisions, creating compliance risk and limiting patient outcomes.

In this article, you will learn:

  • How modern healthcare data pipelines move from paper records to unified digital ecosystems
  • Why ETL processes are critical for clinical data quality and consistency
  • How AI enables real-time processing, predictive analytics and smarter clinical decisions
  • What it takes to build HIPAA-compliant pipelines that balance accessibility with security

Read the full article for a practical look at how AI is reshaping healthcare data infrastructure from the ground up.

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The Complete Guide to AI-Powered Service Management

For enterprises managing complex after-sales operations — across online support, field engineers, and third-party service partners — fragmented tools and manual handoffs are no longer acceptable. This whitepaper introduces ShareService, a unified service management platform that connects every stage of the service lifecycle, from omni-channel intake and intelligent dispatch to on-site field execution, cost settlement, and CSAT analytics. Built on the ShareCRM PaaS infrastructure, ShareService embeds AI agents at each touchpoint: a 24/7 multilingual Online Support Agent that triages and creates work orders in real time, and a Field Service Agent that equips engineers with pre-visit briefings, on-site fault diagnosis, and parts recommendations — reducing return visits and driving consistent service quality at scale.

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AI-Native CRM for Modern Enterprises

As AI reshapes enterprise sales, the question is no longer whether to adopt AI — but whether your CRM can actually support it. ShareAI is an AI-native CRM platform purpose-built for enterprise go-to-market teams, embedding intelligent agents directly across the sales, marketing, and service lifecycle. This whitepaper explores how ShareAI's Agent Studio, Knowledge Platform, and unified data layer enable organizations to automate rep workflows, scale best practices across field teams, and build proprietary AI assets — without exposing customer data to third-party models. From intelligent SDR outreach to AI-assisted field service, ShareAI defines what enterprise CRM looks like in the age of agentic AI.

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A Practical Migration Guide for Enterprises

Replacing a CRM platform is one of the most consequential decisions an enterprise can make — yet for many organizations, the cost and complexity of Salesforce have made the status quo unsustainable. This whitepaper presents a structured migration framework built on 100+ realworld enterprise transitions, showing how organizations in manufacturing, technology services, and consumer goods have successfully moved to ShareCRM while reducing total CRM costs by up to 50%. Readers will gain a clear understanding of why enterprises are reevaluating Salesforce, what a low-disruption migration looks like end-to-end, and how ShareCRM delivers equivalent functionality with a simpler architecture, lower operational burden, and a familiar user experience that eliminates retraining.

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How to Deploy Agentic AI on the Shop Floor—and Scale with Confidence

Ready to move beyond AI pilots? As manufacturing grows more complex and unpredictable, traditional approaches can’t keep up. Before scaling AI, organizations need the right foundation to turn data into real-time, actionable decisions.

In this IDC PeerScape report, discover how manufacturers are deploying agentic AI to connect people, machines, and data—enabling smarter, faster decisions directly on the shop floor. Learn how to move from isolated use cases to a more resilient, adaptive operation.

You’ll learn how to:

  • Turn fragmented data into real-time, guided actions for operators
  • Augment frontline workers with AI-driven decision support
  • Optimize production, scheduling, and resources continuously
  • Automate quality and workflows with intelligent, closed-loop processes

If you’re exploring AI—or ready to scale—it provides a practical roadmap to transform operations and build a more resilient manufacturing business.

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