Build the future of AI-first service

The modern workplace is complex. Even in mid-size companies, employees work across dozens of applications, devices, teams, and environments. They cross IT, HR, finance, and operations boundaries constantly. But when something breaks, when access is delayed, or when onboarding stalls, employees feel every delay and disconnect in the system underneath.

AI was supposed to remove that friction. The promise was simple: deploy an AI agent, deflect tickets, give employees instant answers, and free IT and employee service teams for higher-value work.

Many organizations have learned a harder truth. AI layered on top of a fragmented stack does not remove friction. It often accelerates it. The AI agent answers without context. It can’t complete a request because it can’t access the right asset. The workflow breaks down when IT, HR, and operations data live in different places.

At Freshworks we believe that AI is a force multiplier. It will automate your operations, or it will amplify your chaos. The foundation underneath determines which one you get.

We saw this up close. With 75,000 customers, we have a front-row view of what's actually happening inside service teams—what's working, what's stalling, and where AI is hitting the wall. The blockers weren't ambition. They were disconnected data, missing context, and AI too clunky to adopt or too shallow to trust.

That customer intimacy gave us conviction on what an AI-powered service platform, built for agile enterprises, actually had to deliver.

It had to have depth and scale: AI grounded in a unified platform that handles service, assets, incidents, and operations, trained on more than a decade of real service data and the workflows of agile enterprises running against giants. 

It had to deliver ease: configuration, not coding; deployments live in weeks, not quarters. 

It had to give teams choice: modular by design, with the freedom to start where the need is, use our agents, build their own, or bring their favorite. 

And it had to earn trust: transparent pricing, clear governance, grounded responses, and control that stays firmly in our customers' hands.

Depth and scale, ease, choice, trust. Those four beliefs shaped what we built: a unified platform, with domain-specialized AI, that delivers rapid impact and can be trusted to perform at scale. Four pillars. And today, we're proud to announce groundbreaking innovations across every one of them.

Introducing the next chapter for Freshservice: AI service operations

AI service operations brings service management, operations management, asset intelligence, and AI together into one connected system. It’s built to remove workplace friction so employees get help faster, teams work with better context, and organizations move from reactive support toward proactive service operations.

This launch reflects the principles that shape how we build at Freshworks.

Unified platform

For too long, service, operations, and assets have lived in separate worlds. The service desk handled tickets. Operations handled incidents. Asset management sat in another system. Each had its own data, workflow, and language.

Freshservice brings those worlds together. With ITSM, ITAM, and ITOM on one platform, teams work from the same source of truth for tickets, assets, incidents, services, and workflows. We call this a “Unified Service Operations” platform.

Our reimagined IT asset management, built for Device42’s discovery capabilities and now natively embedded within Freshservice, gives teams a live view of assets across cloud, on-prem, and hybrid environments. Dependency mapping shows what is connected and what could be affected when something changes. FireHydrant, a modern incident management platform we acquired earlier this year, brings unified response operations into the same ecosystem, connecting engineering and IT around major incidents, runbooks, communications, and resolution.

When those pieces operate together, service teams stop stitching context across tools. They can see what is happening, understand the impact, and act with confidence.

Domain-specialized AI 

Service work is not generic, so the AI that supports it cannot be generic either. Freshworks AI is built on years of service data, workflows, and operating patterns across tens of thousands of customers. It understands the difference between a password reset and a privileged access request. It can use service history, asset context, policies, and workflows to recommend next steps or take action safely.

With Freddy AI Agent Studio, we are moving AI from assistance to execution. Teams can create and manage domain-specific AI agents for IT, HR, and other business functions. Prebuilt agents handle access provisioning, password resets, policy questions, and leave requests. A no-code builder lets teams extend that capability without waiting on engineering.

AI-powered HR service delivery brings case management, lifecycle workflows, and Freddy AI HR agents into one experience. Employees should not have to know whether a request belongs to IT or HR. They should get help quickly, without repeating themselves.

We know AI will play a central role in service, which is why customers need the flexibility to choose how they build and extend it on their own terms. MCP Gateway (in early access) extends this AI layer beyond Freshworks. It brings Freshservice data into the AI tools teams already use and allows Freddy AI Agents to act across external systems through a secure, governed gateway.

Rapid impact 

Technology is moving too quickly for 12-month implementations. Teams need to be live, learning, and delivering value, in weeks—not quarters. That is why our AI innovations are designed for no-code setup, prebuilt workflows, and fast adoption.

Freddy AI Agent Studio provides seamless entry into the AI Agent-led help. Executive Overview Insights and Conversational Insights offer real-time views of service health, trends, and root-cause signals. 

Complementing our AI innovations, we are launching XLAs, operating signals that teams using AI tools need to improve continuously. XLAs move service measurement beyond SLA compliance and toward what employees actually experience: reliability, quality, and effort.  

These new service capabilities help teams start where the need is visible, prove value quickly, and expand from there. 

Learn more about the latest product innovations from Freshworks

Trust

The more AI does, the more accountability matters. When we started our AI journey nearly a decade ago, we knew trust would be key to helping people adopt new ways of working that are faster and easier than what came before. 

That belief still shapes how we build Freddy AI at Freshworks, with clear boundaries around data use, grounded and auditable responses, and systems that keep actions visible, decisions traceable, and control firmly in our customers' hands.

The beginning of something more ambitious

For decades, service operations have been reactive. An employee finds a problem, raises a ticket, waits for resolution, and hopes the same issue does not happen again.

That model is giving way to something better: service operations that are proactive, intelligent, and increasingly invisible to the employee. AI detects signals earlier, resolves routine work faster, and learns from each interaction. Human teams guide outcomes, manage exceptions, and improve the system over time.

That future does not come from bolting AI onto fragmented tools. It comes from building the right foundation that has depth and scale, is easy to use, flexible, and open to other intelligent systems, and is delivered by a platform you can trust. 

That is what we are building with Freshservice AI Service Operations: a foundation where employees get help faster, teams operate with more confidence, and service continuously improves.

AI is already changing how service work gets done as organizations shift from reactive support to proactive, AI-driven operations. But direction alone isn’t enough. The harder question is how to actually build toward it.

Most teams are working within systems that have grown over time, shaped by new tools, workflows, and demands. Adding AI into that environment without rethinking how everything connects leads to partial gains at best. Some tasks get faster, but the underlying friction remains.

Real progress comes from taking a different approach and building a system where data is connected, workflows are coordinated, and AI can act with the context it needs. This approach comes down to a few core ideas: bringing the system together, applying AI where it can act, getting to value quickly, and building in the control to scale it.

This launch is how we’ve done that. We’re bringing together a unified platform and AI that can actually operate within it. Here’s what that looks like in practice.

Build on a system where service and operations seamlessly connect

Most service environments weren’t built for AI. Data is scattered, workflows break across teams, and context gets lost between systems. When that happens, AI accelerates the work but not the outcome.

This launch brings service, operations, and asset intelligence into one system so teams can act with full context instead of stitching it together. Tickets, infrastructure, and assets now operate from the same foundation, extending across IT and business teams. When something breaks, the dependency, the impact, and the resolution path are already visible.

That foundation removes the need to rebuild before you start. Teams can move quickly, resolve issues with clarity, and expand without introducing new seams.

AI built to operate across your service environment

AI creates value when it can act. Service work is complex, and generic automation breaks down quickly once real conditions show up.

We’ve built AI that is grounded in service workflows, data, and context so it can resolve requests and take action across systems. It operates across a wide range of service workflows, not just isolated use cases, and improves as it’s used.

Because it’s built into the platform, teams can deploy it quickly without heavy setup, see results early, and expand its role over time. Every action is governed, traceable, and auditable, so teams can scale AI with visibility and control.

Kickstart your shift to AI-first service

This launch brings together a unified platform and trusted AI that can operate within it. Teams can start quickly, improve continuously, and scale with confidence without adding complexity underneath.

The next move is yours. Are you ready?