Hatz AI vs Thread
Side-by-side trajectory, velocity, and editorial themes.
Hatz AI is building the AI workspace for MSPs — per-message model routing, tenant tooling, custom MCP.
Hatz AI is shipping at a high cadence across three connected themes. First, model routing: Auto-LLM picks the right model per message based on task and tools, then layered into Lite, Performance, and Turbo tiers; the catalog keeps adding models (Opus 4.7, Gemini 3.5 Flash, Gemini 3.1 Flash Lite, Gemma 4) with per-model credit multipliers surfaced in the UI. Second, MSP control plane: bulk tenant creation via CSV, custom roles with credit limits, workshop access controls, and embedded support chat in the admin dashboard. Third, surface expansion: audio uploads with auto-transcription, image generation in workflows, file output attaching to chats, 60+ supported file types, speech-to-text in chat, and a steady cadence of integrations and custom MCP server improvements.
The product is taking shape as a multi-tenant AI workspace tuned for MSPs and partner-led delivery — the tenant CSV, credit limits, and workshop sharing are unusual for a generalist AI tool and tell you who buys this. Auto-LLM and tiered routing make sense in that context: an MSP needs cost control across many tenants without micromanaging model picks. Custom MCP and the broad integration cadence position Hatz as a tools-aggregator over multiple LLMs rather than a model wrapper.
Expect more MSP-centric controls — per-tenant budgets, white-label theming, billing reconciliation — and Auto-LLM to grow visible routing telemetry so MSP admins can see why a given model was picked. The custom MCP surface is likely to evolve toward a marketplace pattern with shareable MCP packages across tenants.
Thread keeps deepening Magic's triage agent and tightening Voice AI controls for MSP shops.
Thread's recent cadence centers on iterative Magic AI releases (2.25 through 2.4) that broaden integrations (Hudu, Pia SmartForms), expand the triage agent into multi-step workflows, and polish the operator-facing emulator and settings UX. Voice AI is getting its own thread of refinements around overflow handling and per-agent contact mapping.
The product is being shaped into an integrated triage-and-resolution stack rather than an autocomplete-style assistant: the Magic agents are increasingly trusted to drive conversations to closure, route to the right knowledge source, and recover gracefully when a human is unavailable. Tooling for technicians (folders, resizable panels, emulator) is keeping pace so day-to-day operators can keep up with the agent's expanding scope.
Expect more knowledge-source integrations to land alongside the Hudu path, and the Pia SmartForms pattern to generalize into other PSA actions that the agent can run to completion. Voice AI will likely see additional overflow and handoff logic before a marketed 'agent handles the whole ticket' moment.
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