Agiloft vs Hatz AI
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.
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.
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