Feature Requests

Getting requests from clients for this: Is there a way to integrate Hatz into Excel or PowerPoint so I don’t have to upload files - similarly to how you can do it with Claude?

Request: Add TypeSafe AI's Jev to Hatz as a selectable model, in its own "System One" category separate from the chat/LLM models. What Jev is: Jev (released Sept 15, 2026, early access) is TypeSafe AI's first "System One" model. It doesn't generate text. You give it state plus typed questions, and it returns structured answers (choices, scores, yes/no) with calibrated confidence. All questions are answered in parallel in a single pass. Why it matters: Cost: $0.042 per million input tokens, output is free. That's a small fraction of what we burn today using full LLMs for simple decisions. Speed: TypeSafe reports 40-200x faster than frontier LLMs on decision tasks, with responses in the 70-500 ms range. Reliability: output is constrained to the answer set you define, so there's no free-text parsing and no "creative" answers breaking a workflow. MSP use cases (we'd use these immediately at Innovative): Ticket triage: classify queue, priority, issue type, and sub-issue type on inbound PSA tickets Alert filtering: decide whether an RMM alert is actionable before it becomes a ticket Routing: pick which Hatz model/agent should handle a request, cheap model for simple tasks, capable model for complex ones Security: phishing/spam verdicts on user-reported emails Guardrails: score or flag LLM output before it goes to a client Why a separate category: Jev is a decision engine, not a chat model. Putting it in the normal model picker would confuse users expecting text back. A "System One" category makes it clear it's meant for workflows, agents, and automations, where it pairs with a generative model instead of replacing one. Access: available via TypeSafe's API, LangChain (TypeSafeClassifier), and Vercel AI Gateway.

Heavy users of other LLMs will want a seamless integration from their personal AI of choice into Hatz. Currently there is no migration at all. Processes are extremely manual. Most LLMs have built in channels for digesting context and chat feeds from other LLMs.

As an MSP when I look at the Hatz.AI invoice, I am unable to determine which line item is for which client. It becomes a hassel to map the licenses to the clients. Need the ability to have the tenant names in the invoice so I can bill my clients appropriately.

Including data such as PHI or structured data that contains SSN# DOB Medical diagnosis combined with PII

Providing a mobile-friendly version or dedicated app for the platform would allow users to access tools and features on the go, ensuring flexibility and convenience across devices. Request from PCH Customer

Problem: Our technicians frequently use Microsoft Teams for communication, collaboration, and incident resolution. While Hatz.AI 's chat and agent functionalities are incredibly valuable for accessing information, troubleshooting, and generating solutions, there's currently a disconnect. Technicians often have to switch between Teams and the Hatz.AI platform to leverage AI assistance. This context switching disrupts their workflow, adds friction, and can delay resolution, especially when dealing with complex problems that require rapid access to AI-driven insights during ongoing conversations. Proposed Solution: We request the development of an official integration that allows Hatz.AI 's AI chat and agent capabilities to be seamlessly accessible directly within Microsoft Teams. This could manifest as: A Teams App: A dedicated Hatz.AI app within Teams where technicians can initiate chats with the AI, access specific agents, or trigger AI actions without leaving the Teams interface. A Teams Bot: A Hatz.AI bot that can be invoked within team channels or private chats to answer questions, provide information, or perform tasks using Hatz.AI 's underlying AI models. Message Extensions/Connectors: The ability to highlight text in a Teams conversation and send it to Hatz.AI for analysis, summarization, or to generate a response, which can then be inserted back into the chat. Expected Benefits: Implementing this integration would significantly enhance the value and usability of Hatz.AI for our organization, leading to: Improved AI Usage & Adoption: By making Hatz.AI readily available within their primary communication tool, technicians will naturally integrate AI assistance into their daily workflow, increasing overall AI adoption. Streamlined Workflows & Productivity: Eliminating the need to switch applications reduces context-switching overhead, allowing technicians to stay focused and work more efficiently. Faster Problem Resolution: Technicians can get instant AI assistance for complex issues directly within their resolution conversations, accelerating troubleshooting and decision-making. Enhanced Collaboration: AI-generated insights and solutions can be easily shared and discussed within Teams channels, fostering better collaboration and knowledge sharing among team members. Reduced Training Burden: Integrating AI into a familiar environment like Teams may reduce the learning curve for new users and encourage broader utilization. We believe this integration would be a game-changer for improving technician efficiency, leveraging Hatz.AI 's power more effectively, and ultimately leading to faster and more consistent problem resolution across our operations.

Can we get that 50mb file limit upload increased? Thanks!

Would be great to have a geo location in a Canadian AWS DC to hit the data residency requirements of a lot of Canadian companies.

In order to keep track of which tenants templates have been shared with would be helpful.