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Comparison · Support

Front vs Hatz AI

Side-by-side trajectory, velocity, and editorial themes.

Front logo
Front
SUPPORTCOLLAB
2.5

Front is rebuilding the shared inbox around AI agents and omnichannel reach.

◆ Current state

Front is a team inbox that has pivoted its roadmap toward AI: Copilot/Autopilot replies, knowledge-source ingestion, and admin controls over what the AI can cite. Alongside that it keeps widening its integration surface—Salesforce, Asana, Zoom Contact Center, and a steady stream of third-party AI tools—so more channels and systems route through one workspace.

◆ Where it's heading

The direction is to make Front the front end for AI-assisted support across every channel, with admins given finer governance over what the AI knows and does. Recent work layers in file-based knowledge, fact invalidation, and ROI analytics for Autopilot—signs Front is moving from 'AI that drafts' toward 'AI teams can trust and measure.'

◆ Prediction

Expect the 'bring your own agent' survey and BYOA early access to harden into a shipped capability, letting customers plug external AI agents into Front's inbox and channels.

H
Hatz AI
SUPPORT
6.3

Hatz turns its MSP AI platform into an agent-composition and phone-automation system.

◆ Current state

Hatz AI is an MSP-oriented AI workspace: a governed model selector plus agents, workflows, integrations, and AI phone agents, sold through managed-service-provider tenancy. Recent releases push hard on two fronts: making phone agents a real front-line call system (routing, warm transfer, caller memory, business hours, post-call workflows) and making agents composable inside workflows. Model breadth keeps expanding, with Sonnet 5 and seven new LLMs added to the selector.

◆ Where it's heading

The direction is from a chat-with-models tool toward an automation platform where saved agents are reusable building blocks and phone agents replace human triage. Governance is a throughline: role-based model, integration, and tool controls, tenant templates, and usage budgets all deepen the MSP multi-tenant control plane. Model selection is increasingly abstracted behind Auto-LLM.

◆ Prediction

Expect further phone-agent autonomy and more agent-as-step composition across workflows, with continued MSP governance controls and ongoing additions to the model roster.

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