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Monthly releases on time, security out-of-band, and the changelog living somewhere else
A side-by-side editorial comparison of Hiver and Hatz AI — release velocity, themes, recent moves, and the top alternatives to consider.
| Feature | Hiver | Hatz AI |
|---|---|---|
| Sector | Support | Support |
| Velocity score | 0.0 | 6.3 |
| Sparks · 30d | 0 | 1 |
| Top themes | customer-support, gmail, ai-knowledge, omnichannel | msp tooling, model aggregation, voice agents, usage-based pricing |
| Last editorial update | 1d ago | 1d ago |
| Website | Visit → | — |
Gmail-based support tooling wiring internal docs into its AI and unifying search across channels
Hiver's April releases center on grounding its AI in a company's own material. Confluence pages, Google Docs and Google Sheets can be added as knowledge sources, and Ask AI can query an uploaded Sheet directly — answering questions like top customers by revenue without manual analysis. Alongside that, Omnichannel Search spans email, chat and Slack with unified results and channel attribution, and automations gained a trigger for conversations moved into a shared inbox. Each release appears twice in the feed.
Hatz adds every frontier model within days, and just dropped the license gate on its Phone Agent
Hatz runs two tracks. One is model breadth: Kimi K3, GLM 5.2 Fast, Claude Opus 5, Gemini 3.6 Flash and 3.5 Flash-Lite, Grok 4.5, GPT-5.6 and Fable 5 all reached the model selector within weeks of release, across chats, apps, agents and workflows. The other is the MSP-facing product — a Phone Agent that gained caller memory, business hours, call-length limits and a redesigned setup flow, plus credit usage reporting, workshop content and team management. AutoTool v2 improves how reliably agents pick and recover tools mid-conversation.
Hiver's April releases center on grounding its AI in a company's own material. Confluence pages, Google Docs and Google Sheets can be added as knowledge sources, and Ask AI can query an uploaded Sheet directly — answering questions like top customers by revenue without manual analysis. Alongside that, Omnichannel Search spans email, chat and Slack with unified results and channel attribution, and automations gained a trigger for conversations moved into a shared inbox. Each release appears twice in the feed.
The product is extending past the shared-inbox job into being the place a support agent finds any answer. Knowledge sources make the AI useful on internal SOPs rather than generic replies; omnichannel search makes prior context findable regardless of where the conversation happened. Both reduce the reasons an agent leaves Gmail, which is the whole premise Hiver sells on.
Expect more knowledge source connectors on the pattern set by Drive and Confluence, since the Sheets query capability shows the ingestion path already handles structured as well as prose content.
Hatz runs two tracks. One is model breadth: Kimi K3, GLM 5.2 Fast, Claude Opus 5, Gemini 3.6 Flash and 3.5 Flash-Lite, Grok 4.5, GPT-5.6 and Fable 5 all reached the model selector within weeks of release, across chats, apps, agents and workflows. The other is the MSP-facing product — a Phone Agent that gained caller memory, business hours, call-length limits and a redesigned setup flow, plus credit usage reporting, workshop content and team management. AutoTool v2 improves how reliably agents pick and recover tools mid-conversation.
The model-aggregation track is a treadmill Hatz appears committed to running — being current is the feature, and each addition is integration work rather than a strategic choice. The real product effort is concentrated in the Phone Agent and the MSP layer around it, and replacing the license requirement with usage-based pricing points at getting far more MSPs to try it. AutoTool defaulting to on in new chats fits the same pattern: remove the setup a customer has to think about.
Expect model additions to continue at this pace with little strategic weight attached, and the Phone Agent to keep absorbing the roadmap now that a license no longer gates it. The credit usage reporting suggests per-tenant cost visibility is the next MSP concern being addressed.
Other Support products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either Hiver or Hatz AI.
Monthly releases on time, security out-of-band, and the changelog living somewhere else
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The cloud edition's log is mostly repair work, much of it inherited from its on-prem twin.
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See all Hiver alternatives → · See all Hatz AI alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. Hatz AI is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Hatz AI is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Support products to evaluate alongside.
Top Hiver alternatives in Support are ranked by recent ship velocity. Browse the "Hiver alternatives" section above for the current picks, or visit /alternatives/hiver for the full list with editorial commentary on each.
Top Hatz AI alternatives in Support are ranked by recent ship velocity. Browse the "Hatz AI alternatives" section above for the current picks, or visit /alternatives/hatz-ai for the full list with editorial commentary on each.