Front vs Hatz AI
Side-by-side trajectory, velocity, and editorial themes.
Front is rebuilding the shared inbox around AI agents and omnichannel reach.
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.
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.'
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.
Hatz turns its MSP AI platform into an agent-composition and phone-automation system.
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.
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.
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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