Service Desk for the AI Era.

AI in a service desk is not about replacing people. It is about improving user experience and giving your technicians a real productivity edge. Helena AI is built directly into DeskDay, not bolted on top, so every ticket benefits from intelligence from the moment it arrives.

Auto intake

Every ticket is reviewed and updated with the right context & details automatically, so your team can start troubleshooting immediately.

Auto triaging

Every incoming ticket is automatically categorised, prioritised, and tagged so your team skips the sorting and jumps straight to resolving.

Intelligent routing

Helena reads ticket context and routes each request to the right technician or team, based on skill, workload, and history.

KB Surfacing

Relevant knowledge base articles are automatically surfaced inside the ticket, so techs and users get answers without hunting for them.

Historical ticket suggestion

Similar issues resolved before? Helena surfaces them instantly, giving your team the context and fix without starting from scratch.

Support users with Multi-channel ticketing

Let your users raise tickets from the channels they already use, whether it's Microsoft Teams, Email, Web, Desktop, or Mobile.

Key metrics that matter

3x
Faster resolution with Helena AI
40%
Increase in tech throughput
30%
Higher CSAT scores
<30min
To get up & running
integrations

Integrate with your existing tools

Learn more
Loved Worldwide

Trusted by hundreds of MSPs & IT Teams.

Ready for a Smarter
Service Desk?

Up and running in under 30 minutes. No complex setup. No long contracts.

Frequently asked questions

What is DeskDay?
DeskDay is a Professional Services Automation (PSA) and ticketing platform built for MSPs and IT teams. It brings together a chat-based service desk powered by workflow automation and an AI agent, time tracking, billing, project management, and reporting in one place, with end-user support across Microsoft Teams, mobile, email, web, and desktop channels.
Who is DeskDay built for?
DeskDay is built for MSPs and IT teams who want a modern service desk and PSA without the complexity of legacy tools. It fits solo and growing MSPs, and internal IT departments alike.
How is DeskDay different from legacy PSA tools?
Legacy PSA tools are form-heavy, fragmented, and slow, built from years of stitched-together modules where chat and AI are bolted on as afterthoughts. DeskDay is built the opposite way. It’s chat-first, AI-assisted, and intuitive by design, shaped around how MSP techs and IT teams actually work day to day. Conversations, automation, and AI are native from day one, not add-ons, which is why DeskDay feels simpler, faster, and easier to use. Most MSPs are up and running in days, not months, without the long onboarding cycles or heavy configuration that come with legacy PSA platforms.
How fast can an MSP or an IT Team get started with DeskDay?
Most MSPs/IT Teams are live within days. DeskDay is designed for quick onboarding, with guided setup and no long implementation cycles.
What core problem does DeskDay solve for MSPs and IT Teams?
DeskDay removes the silos and complexity MSPs/IT Teams struggle with. Tickets, chats, workflows, AI, and billing live in one system instead of being stitched together across tools that don’t talk to each other.
What integrations does DeskDay support?
DeskDay connects with major RMM tools like NinjaOne, Datto, N-able N-central, and Level. Accounting and documentation tools like QuickBooks, Xero, and Hudu are also supported, with more integrations on the way.
How do customers raise tickets in DeskDay?
Customers can raise tickets and chat with their assigned techs from Microsoft Teams, email, web, desktop, or mobile. Every channel flows into a single service desk for techs, so nothing gets missed or fragmented.
How easy is DeskDay to use compared to legacy PSAs?
DeskDay is designed to be intuitive from the first login, unlike legacy PSAs.
How does DeskDay leverage AI?
Helena, DeskDay’s AI agent, helps techs draft replies, suggest past ticket resolutions and relevant KB documents, and detect customer sentiment; cutting tech workload while keeping documents accurate.