AI for IT Support & Managed Service Providers

Unlike traditional helpdesks that queue tickets for human agents, our AI resolves common issues instantly through natural conversation. It understands technical context, walks users through troubleshooting steps, and only escalates to human engineers when genuinely needed. The AI learns from every resolved ticket, continuously improving its accuracy and expanding the range of issues it can handle autonomously.

Yes, we provide deep two-way integration with ConnectWise Manage, Autotask, and other major PSA platforms. The AI creates tickets with full categorisation and priority, updates ticket status in real-time, logs time entries, and reads configuration items and client data. All interactions are synced bi-directionally so your engineers always have complete context when they pick up an escalated ticket.

Absolutely. Our AI resolves the top ticket types that consume the majority of Level 1 time: password resets, account lockouts, VPN connectivity, printer issues, Microsoft 365 questions, and basic software troubleshooting. It follows your exact runbooks and SOPs, collects all required diagnostic information, and achieves 85% first-contact resolution. For issues it cannot resolve, it escalates with comprehensive notes that save your engineers significant investigation time.

The AI follows strict identity verification workflows before processing any security-sensitive request. It can verify users through multi-factor authentication, security questions, manager approval workflows, or integration with your identity provider. All security actions are fully logged with audit trails. The verification process is configurable to match your security policies and can be strengthened for privileged accounts or sensitive systems.

When the AI determines an issue requires human expertise, it performs a warm handover to the appropriate engineer based on skill matching, availability, and client SLA tier. The escalation includes a complete summary of the conversation, diagnostic steps already taken, system information collected, and a recommended next action. This eliminates the frustrating cycle of users repeating information and significantly reduces mean time to resolution on escalated tickets.

The AI monitors every ticket against its applicable SLA tier in real-time. It proactively alerts your team before breaches occur, automatically escalates stalled tickets up the priority chain, and generates compliance reports for client business reviews. By resolving tickets faster and routing them more intelligently, the AI dramatically reduces SLA breach rates. Most MSPs see SLA compliance improve from 85-90% to 98%+ within the first quarter.

Your best engineers did not build their careers to reset passwords all day. AI absorbs the repetitive Level 1 volume - password resets, VPN troubleshooting, printer fixes, basic M365 questions - that consumes 60-70% of a typical helpdesk day. Engineers get back to the infrastructure projects, security improvements, and strategic client work that grows your business and keeps talented people engaged. Most MSPs use AI to scale their client base significantly without proportionally increasing headcount, improving margins while reducing the burnout that drives engineer turnover.

The AI provides full 24/7 helpdesk coverage without on-call fatigue for your team. After hours, it resolves common issues autonomously, creates and categorises tickets for next-business-day follow-up, and only pages your on-call engineer for genuine emergencies based on your configured severity criteria. This means your engineers get uninterrupted rest while your clients receive immediate acknowledgement and resolution for most issues regardless of the time.

Yes, the AI integrates with major RMM platforms including Datto, NinjaOne, ConnectWise Automate, and others. It ingests monitoring alerts, correlates related events to suppress noise, and creates contextualised tickets with relevant system information attached. This transforms the flood of monitoring alerts into actionable, prioritised incidents, reducing alert fatigue and ensuring genuine issues receive immediate attention.

Agree how service tickets and client IT information may be used before connecting any systems. Review each selected provider, the locations of storage and AI processing, retention, access permissions and any onward transfers. Australian-only handling must be confirmed for the complete data flow in the project agreement. Check the relevant provider security evidence and test the configured controls before live use. For MSP use, test tenant separation and permission boundaries before live access. Agree a security testing scope instead of assuming a certification or recurring audit already covers the project.

Most MSPs see positive ROI within 3-4 months. The primary savings come from reducing cost per ticket by 50-60%, eliminating after-hours staffing costs, preventing SLA breach penalties, and enabling scale without proportional headcount growth. A typical MSP with 500 endpoints saves $8,000-$15,000 per month in labour costs alone. The AI also drives revenue growth by enabling faster client onboarding and supporting larger contract commitments with confidence.

MSPs move fast and our deployment matches that pace. Full deployment takes 7-11 weeks: Phase 1 (1-2 weeks) covers helpdesk audit and PSA/RMM integration mapping. Phase 2 (3-4 weeks) deploys Level 1 AI and intelligent ticket triage with shadow mode quality assurance. Phase 3 (3-5 weeks) adds proactive monitoring integration, knowledge base AI, and client self-service. Most MSPs see measurable ticket volume reduction within the first week of Phase 2.

Absolutely. The AI supports multi-tenant configurations with per-client customisation for SLA tiers, escalation policies, knowledge bases, and branding. A VIP client can have immediate escalation rules while standard clients follow normal triage. Each client's configuration is independently managed, ensuring service delivery matches contractual commitments. This flexibility is essential for MSPs managing diverse client portfolios with varying service agreements.

The AI continuously learns from every interaction and resolution. When engineers resolve escalated tickets, those solutions feed back into the AI's knowledge base for future autonomous resolution. Monthly optimisation reviews analyse ticket patterns, resolution rates, and user satisfaction to fine-tune the AI's capabilities. Over time, the AI handles an increasingly broad range of issues, with most deployments seeing autonomous resolution rates improve by 5-10% per quarter.