Modernize Your Business
What Should Software Teams Expect from Remote Support Platforms to Streamline Operations and Safeguard their Brand?
Software and technology teams operate in a high-stakes environment where every customer interaction can impact brand trust, security, and compliance. This blog explores what modern organizations should expect from remote support platforms to keep operations running smoothly while protecting sensitive data. It highlights the risks of outdated tools—from security vulnerabilities to operational inefficiencies—and outlines the critical capabilities today’s teams need, including robust access controls, real-time auditability, and fast, reliable global connectivity. Discover how forward-thinking companies are elevating their support strategy to deliver secure, seamless experiences that safeguard both their customers and their reputation.
Beyond modernization: A CIO’s roadmap to agentic AI transformation
Agentic AI Transformation for Modern Enterprise IT
Modernization is no longer a destination—it’s a continuous journey. As agentic AI reshapes enterprise IT, CIOs must rethink architecture, governance, and legacy systems to support autonomous systems and human-AI collaboration at scale.
Building Enterprise-Ready Agentic AI at Scale
This e-book explores how agentic systems enable organizations to extend and renew existing environments without disruptive rebuilds—delivering the agility, resilience, and speed required to keep pace with constantly changing business demands. It also shows why a unified, agile, and enterprise-proven AI development platform is critical for turning AI ambition into execution.
In this e-book you’ll learn how to:
- Use agentic AI to modernize and extend legacy systems without replacing core platforms
- Build an evergreen architecture that stays stable at the core and evolves at the edges
- Design agent-driven workflows with built-in governance, security, and observability
- Bring AI into the SDLC while avoiding future technical debt and tool sprawl
- Scale AI agents faster using a unified platform that supports rapid iteration and control
- The result is a practical roadmap for CIOs looking to build their agentic future—one that balances speed with safety, innovation with governance, and transformation with enterprise readiness.
AI Agent Orchestration: How to Close the Action Gap and Improve ROI
Why AI agent adoption stalls without agent orchestration
AI adoption stalls when standalone agents lack deep workflow integration, forcing humans to act as "middleware" between insights and execution. This manual friction increases the cost of AI agents and creates a time-to-action lag that prevents measurable AI agent ROI.
Is AI agent orchestration suitable for complex workflows?
AI agent orchestration is specifically designed to handle the complexity that single-prompt models cannot. By acting as a central "conductor," an orchestration layer coordinates multiple specialized agents to share context and collaborate on iterative, multistep planning. This allows organizations to automate sophisticated end-to-end processes while reducing the manual friction that typically stalls AI agent adoption.
Is orchestration part of an AI agent strategy?
Yes, orchestration is the vital link that transforms isolated experiments into production-ready workflows. A mature AI agent strategy uses an orchestration layer to manage agent handoffs and ensure that multi AI agent orchestration aligns with business goals.
Start improving AI agent ROI
Download the full Forrester report, Mind The Agentic Action Gap: Stop Losing Money With AI Agents, to bridge the agentic action gap and transform your AI initiatives into high-ROI strategic assets.
Measure your gap by assessing friction, time to action, and compliance to improve AI agent ROI measurement.
Flip the operating model so agents orchestrate execution while humans shift to high-level oversight.
Master agent experience skills like knowledge curation and critical thinking to accelerate AI agent adoption.
Uncomplicating IT with Freshworks and Fellowmind: AI-Powered Strategies for the Modern Workplace
IT complexity is a growing challenge, and organizations are increasingly turning to AI to gain control and drive efficiency. Join Gorm Priem from Fellowmind and Freshworks experts to learn how AI-powered strategies are helping organizations cut complexity, optimize IT operations, and enhance employee and customer experiences. Discover real-world lessons from Fellowmind’s journey, and walk away with actionable insights to uncomplicate IT in your own organization.
By the numbers: Why LogMeIn Rescue outperforms TeamViewer
Struggling with slow connections, limited device compatibility, or security gaps in your remote IT support solution? It may be time for a smarter approach.
LogMeIn Rescue is built to help support teams resolve issues faster, work more efficiently, and deliver seamless customer experiences—no matter the device, network speed, or environment. Independent testing shows Rescue enables connections up to 2x faster and file transfers over 3x faster, while using significantly less memory than TeamViewer.
Beyond speed, Rescue empowers your team with advanced collaboration tools, support for older operating systems, and enterprise-grade security—including single-use access codes and device-level authentication to keep every session protected.
Whether you're supporting a global workforce or troubleshooting on low-bandwidth connections, Rescue helps you hit your KPIs without compromise.Download this datasheet to learn more.
Embedded Intelligence Loop: Faster Insights Without Moving Your Data
The “Embedded Intelligence Loop” illustrates how modern data platforms integrate analytics, AI, and applications into a continuous, closed-loop system that drives faster and more informed decision-making. By combining Posit’s data science tooling with Databricks’ Data Intelligence Platform, organizations can seamlessly move from data ingestion and exploration to model development, deployment, and real-time feedback. This loop enables users to build and embed intelligent applications directly into business workflows, ensuring insights are continuously refined through usage and new data. The result is a unified, governed environment where data, models, and applications operate together—accelerating innovation, improving collaboration, and turning raw data into actionable, continuously evolving intelligence.
Spring 2026 G2 Grid Report: AI Customer Support Agents
Get the analyst-backed proof behind Fin’s leadership in AI customer support.
In G2’s Spring 2026 Grid Report, Fin by Intercom stands out with top customer satisfaction scores, strong market presence, and rapid time to value.
Access the report to see how real users rate Fin against other leading AI customer support platforms
The Business Value of Intercom and Fin
What does AI-powered customer support look like when it delivers measurable business value?
This IDC study examines how organizations using Intercom and Fin reduced human support volume, improved team efficiency, and elevated the customer experience.
Readers will get a data-backed look at how automation, chat-first support, and AI-driven workflows contributed to stronger productivity and satisfaction outcomes.
The 2026 Customer Service Transformation Report
Customer service is entering its biggest shift in decades — and AI is at the center of it.
But here’s the catch: while nearly everyone is adopting AI, only a small group is actually using it in a way that drives real transformation.
So what separates surface-level automation from mature deployment?
Download this new report from Intercom to uncover:
- Where support teams are seeing the biggest gains from AI
- Why deeper integration leads to clearer ROI
- What the next generation of customer experience will demand in 2026
- How support is becoming the blueprint for AI across the entire business
Don’t just launch AI. Learn how to scale it.
Blueprint Workbook Part 1: Launching an AI Agent
Launching an AI Agent can feel exciting — and risky.
Done well, it changes everything.
Done poorly, it creates customer distrust, internal hesitation, and disappointing results.
So how do you start the right way?
This step-by-step workbook will help you:
- Build a clear business case for AI in support
- Define what success actually looks like (beyond “deflection”)
- Evaluate solutions with confidence
- Deploy your AI Agent with the right tone, guardrails, and handoff experience
If you’re at the beginning of your AI journey, start here
