Agiloft vs Hiver
Side-by-side trajectory, velocity, and editorial themes.
Agiloft is on Release 33 with a steady core/connected-services cadence — feed signal is thin past the version number.
The tracked entries are dominated by scraped release-notes index and cadence boilerplate (Core Platform on a February/July/November functional cadence with monthly maintenance, plus monthly Connected Services). The substantive crumb in the window is that Release 33 has shipped (entry references the move from Release 32), and a UX modernization adding live partial-match typeahead on common field types is visible in the content body of one entry.
Agiloft is operating like a mature enterprise platform — predictable release calendar, monthly maintenance, incremental UX modernization on field types. Whatever AI/CLM-AI work is in motion isn't visible through this feed shape. The product is being shipped, but the changelog scraper is mostly catching index pages rather than the meaningful per-feature notes.
Realistically the next visible move will be Release 34 with the July functional bundle, plus Connected Services rollouts each month between now and then. The bigger question — whether Agiloft has an answer to the agentic-CLM motion at Ironclad and Sirion — can't be read out of the current feed.
Hiver pivots from Gmail-only to AI-grounded omnichannel.
The recent feed shows two parallel pushes: an AI knowledge layer (Google Drive, Confluence, and Google Sheets becoming Ask-AI-queryable sources) and a channel-expansion push (Slack as a managed customer-service channel inside Hiver Omni, plus omnichannel search and automation primitives that work across email/chat/Slack). Automation gets meaningful new building blocks too — API calls as actions, new triggers and conditions.
Hiver is repositioning from 'shared inboxes inside Gmail' to 'AI-grounded omnichannel customer service platform.' The Slack-as-channel and API-call automation moves directly compete with Front, Help Scout, and the lightweight tier of Zendesk. The AI knowledge-source work is laying the grounding layer that turns Hiver AI from a reply-suggester into something closer to a tier-1 agent.
Expect a Microsoft Teams channel addition, more knowledge-source connectors (Notion, SharePoint, Salesforce KB), and a packaged 'AI Agent' tier that bundles Ask AI + grounded sources + automation actions into something that resolves tickets autonomously. Pricing for AI usage is the next question — flat seats won't survive heavy Ask-AI workloads on customer data.
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