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Comparison · Support

SupportBee vs Hatz AI

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

S
SupportBee
SUPPORT
0.0

SupportBee's public changelog hasn't moved since 2019 — the product appears dormant.

◆ Current state

All four ingested SupportBee entries are from early 2019: a UI refresh, an autocomplete tweak in the ticket reply form, a Customer Groups feature for the Enterprise plan, and the meta-announcement of starting a changelog. There has been no public release activity in the seven years since.

◆ Where it's heading

There is no observable trajectory. The 2019-only entries suggest the product is either in deep maintenance mode or has stopped publishing externally. Whatever direction SupportBee took post-2019 isn't visible from the public release notes.

◆ Prediction

Without fresh signal, no confident prediction is possible. The likely scenarios are continued maintenance for an existing customer base or eventual sunset; the data here cannot disambiguate.

H
Hatz AI
SUPPORT
6.3

Hatz AI is building the AI workspace for MSPs — per-message model routing, tenant tooling, custom MCP.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

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