Infobip vs Hatz AI
Side-by-side trajectory, velocity, and editorial themes.
Infobip is rebuilding its CPaaS stack around AI agents, MCP servers, and AgentOS.
Recent quarterly updates (Q3 and Q4 2025, Q1 2026) frame a consistent direction: AI as a first-class layer of customer-communications infrastructure, with AgentOS unifying agent management and MCP servers exposing telephony and messaging channels to LLM-driven agents. Surrounding the AI work are channel upgrades (WhatsApp Business Calling, RCS onboarding, Vocalize voice) and CDP/CRM integration depth. The crawler captured a lot of page chrome — most of the recent feed is generic CTAs and section headers — but the substantive entries paint a clear AI-CPaaS thesis.
Infobip is racing Twilio, Bandwidth and Sinch to define what 'AI-native CPaaS' actually looks like. The MCP server angle is the most interesting bet: if it sticks, every AI agent build becomes a potential Infobip integration, not just contact-center vendors. Expect continued packaging of channel + AI bundles aimed at enterprise buyers who want one vendor for both.
The next observable moves will be more named integrations between AgentOS and major LLM platforms, additional MCP server coverage across remaining channels (email, voice IVR), and a reference architecture for autonomous customer-service agents that handle real transactions, not just FAQs.
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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