Overview

What is Hatz AI?

Hatz AI is an AI platform for small and mid-sized businesses, delivered entirely through the managed service providers those businesses already work with. Its publisher, Hatz AI, Inc., calls it an AI operating system for the SMB market: the partner provisions the tenant, decides the packaging and the price, and remains the customer's point of contact, while Hatz supplies the platform underneath.

Three building blocks make up the product. Secure Chat is a multi-model assistant with access to more than 65 large language models from thirteen labs, among them Amazon, Anthropic, DeepSeek, Google, Meta, Mistral, NVIDIA, OpenAI, Qwen and xAI. It offers automatic model selection, mid-conversation model switching, folders, shareable artifacts, memory and personalisation, sub-agents, speech-to-text and image generation. The Workshop is where teams assemble three kinds of object without writing code: apps, multi-step workflows and agents. A build assistant turns a plain-language brief into a working item. Agents take instructions, knowledge sources, tools, file and folder scoping, and even their own email address; workflows can be scheduled or fired by an HTTP webhook from an external system, and include document-processing steps and exports. The third block is the AI Phone Agent, which handles voice calls, applies a blocklist and can run a workflow after every call.

A separate module, Hatz Activate, is aimed at the partner rather than the end user. It pulls PSA exports and CSV files into a single customer table, flags where unsanctioned AI tools are already in play across a client base, and tracks each rollout from Not Sent through Sent to Activated on a live conversion dashboard.

Usage is metered in Hatz Credits, allocated monthly at tenant level and shared between users; they reset each calendar month and do not carry over. Data sits in AWS data centres in Virginia, separated by tenant, organisation and user, with the inference layer deliberately kept apart from stored history. Forty-four documented integrations span the MSP stack and everyday business tools, custom MCP servers are supported, and an API with per-user keys is documented separately.

What it does

  • Run secure chat across more than 65 large language models with automatic model selection
  • Build apps, multi-step workflows and AI agents without writing code
  • Connect existing business tools such as Microsoft 365, ConnectWise Manage, HubSpot and Slack
  • Trigger workflows on a schedule, by HTTP webhook or from a dedicated agent email address
  • Answer and handle inbound phone calls with an AI voice agent and a post-call workflow
  • Administer multiple client tenants with roles, credit limits and audit logging
  • Surface unsanctioned shadow AI usage across a client base and track rollout progress
Audience

When to use Hatz AI / When not to

A quick filter to help you decide if Hatz AI is the right fit.

When to use Hatz AI

  • Managed service providers wanting to resell white-labelled AI to an existing base of SMB clients
  • Small and mid-sized businesses already working with an MSP that want AI without building their own governance
  • IT support and NOC teams handling ticket triage, scripting and client onboarding or offboarding
  • Operations, marketing, legal and finance teams inside one company that want a single sanctioned AI workspace
  • Buyers whose procurement requires SOC 2 Type II attestation and a documented no-training policy

When not to use Hatz AI

  • Individuals, freelancers and small teams with no MSP relationship, since there is no self-service sign-up
  • Anyone handling protected health information, as Hatz supports neither HIPAA compliance nor Business Associate Agreements
  • Buyers who need a published price list before starting a conversation with a vendor
  • Organisations that must keep data resident in the European Union, as everything is hosted in the United States
  • Users under 18, for whom the services are explicitly not intended
Get started

How to use Hatz AI

A typical end-to-end flow, from setup to results.

  1. Apply for partnership on the Hatz website; the team typically responds the same day
  2. Complete the self-service training modules and the certification tracks for AI knowledge, product usage, administration and sales
  3. Get access to the multi-tenant administrative portal and the help centre documentation
  4. Use the Not For Resale package internally first, to learn the platform before selling it
  5. Provision a client tenant, choose its package and credit allowance, and send user invitations
  6. Log in to the client workspace and start with Secure Chat, letting automatic model selection pick the model
  7. Enable the integrations the client already uses from the customer dashboard, activating beta connectors explicitly where needed
  8. Describe the goal in plain language to the Workshop Assistant, which builds the app, workflow or agent
  9. Publish each Workshop item and control access through Groups
  10. Automate the result with workflow triggers or an HTTP webhook, then monitor consumption on the Workspace Usage Dashboard
Quick read

Pros & Cons

Pros

  • More than 65 models from thirteen labs behind one interface, with the ability to switch mid-conversation
  • An unconditional no-training policy on customer data, contractually extended to the underlying LLM providers
  • SOC 2 Type I and Type II plus SOC 3, backed by regular penetration testing and external security reviews
  • Logical isolation by tenant, organisation and user, with the inference layer separated from stored history
  • Broad integration coverage of both the MSP stack and everyday business tools, plus custom MCP servers
  • No-code construction of apps, workflows and agents from a plain-language brief
  • A local MSP partner providing training, certification and hands-on support rather than a ticket queue

Cons

  • No published pricing at all, which makes comparison impossible without engaging a partner
  • No direct purchase and no self-service sign-up: every customer must go through the partner network
  • No HIPAA compliance and no Business Associate Agreement, so protected health information is off limits
  • Hosting only in the United States, with no announced EU data residency option
  • No published subprocessor list, no public data processing agreement and no Article 27 EU representative
  • A single published contact address and no postal address anywhere on the site
  • Monthly credits do not carry over, and they are consumed even when a later workflow step fails
Pricing

Pricing & Plans

No pricing is published. Hatz AI is sold exclusively through its network of MSP partners, each of which sets its own packaging and price, so no entry-level amount or currency can be stated. There is no advertised permanent free plan and no self-service trial; the terms of use merely frame any free trial or promotion a partner may be granted, without confirming that one exists. Usage is metered in Hatz Credits, allocated monthly per tenant and shared across users. The documented orders of magnitude are useful for budgeting: a typical chat consumes between 1 and 30 credits, and summarising an A4 page into roughly 100 words costs between 1 and 12 credits. Unused credits do not carry over, an Extra Usage mechanism allows a tenant to exceed its allowance, and the AI Phone Agent is billed per minute with a monthly minimum.

Tenant packages
  • each client tenant is assigned a package carrying a monthly credit allowance
  • with documented upgrade and downgrade paths. Neither the tier names nor their prices are published
  • and the final price is set by the MSP partner.
NFR (Not For Resale) packages
  • reserved for Hatz partners for internal use
  • demonstrations and testing rather than resale.
Special offers — Not For Resale (NFR) packages for Hatz partners, intended for internal use, demonstrations and testing rather than resale
Prices and plans listed above may evolve. Always check the official pricing page before subscribing.
Trust & Privacy

Data, GDPR & hosting

A consolidated view of how Hatz AI handles your data.

GDPR overview

The privacy policy, last updated on 3 February 2026, engages with the GDPR in concrete terms rather than in passing. It names the Article 6 legal bases used — consent, legitimate interests, contract performance and legal obligations — and lists the rights available to residents of the EEA, the United Kingdom and Switzerland, including access, rectification, erasure, objection, portability, withdrawal of consent and complaint to a supervisory authority. Transfers are addressed directly: servers sit in the United States and Standard Contractual Clauses are cited as the safeguard. Requests are routed first through the customer's MSP, or directly to help@hatz.ai. Three gaps remain visible: no Article 27 EU representative is designated, no data protection officer is named, and no subprocessor list or data processing agreement is published.

Who owns the data?

Customers keep ownership. The End Customer Terms state that Hatz AI claims no ownership of End Customer Data, including uploaded documents, prompts and generated outputs, and the Terms of Use confirm that MSP Content stays the exclusive property of the MSP. Hatz receives only a limited, non-exclusive, revocable licence to process that data in order to deliver the service through the MSP, and it is expressly barred from using it to train or improve models for other customers. Two carve-outs matter: operational and usage data such as logs, volumes and workflow metadata belong to Hatz, and Hatz holds a perpetual right to aggregate and anonymise MSP Content for product improvement and benchmarking.

Reuse rights

End users may reuse their own inputs and the outputs the platform generates without asking Hatz for permission: as between the parties, the customer owns all right, title and interest in that material, and Hatz creates no derivative works beyond the outputs the user requested. The terms are honest about the limits of that freedom, however. Outputs are delivered as is, with no warranty of accuracy, completeness or timeliness; the same or a similar output may be produced for another customer, and the customer has no claim over what other users receive; Hatz makes no representation that outputs are protectable by intellectual property rights, nor that they avoid infringing someone else's. Commercial reuse is therefore permitted but sits entirely at the customer's own risk, and feedback sent to Hatz about the product is separately licensed to Hatz on a perpetual, irrevocable basis, although normal working data such as queries and uploaded documents is explicitly excluded from that feedback licence.

Data retention & training

Retention summary
For website visitors and event attendees, personal information is kept for the duration of the business relationship plus whatever the law requires. For platform users, operational data and metadata are retained as long as access exists, then for a reasonable period afterwards for legal, audit or operational reasons. The content of documents, queries and AI interactions is not stored beyond what delivering the service requires. Retention of End Customer Data itself follows the agreement with Hatz or with the MSP. Anonymised, aggregated data may be kept indefinitely for analytics. After a contract ends, MSP Content stays retrievable on the platform for fifteen days, or is deleted sooner on request. LLM providers may hold anonymised data briefly for abuse monitoring, then delete it. No retention period is published in days for logs or backups.
Trains on customer data
No
GDPR contact

Hosting summary

All conversation histories, user settings and organisational data are held in secured AWS data centres in Virginia, in the United States, logically separated by tenant, organisation and user. The privacy policy confirms that the servers sit in the United States and that service providers in other countries may be involved; for transfers from the European Economic Area, the United Kingdom or Switzerland, Standard Contractual Clauses are cited as the safeguard. The architecture deliberately separates the inference layer from stored history, so the models hold no persistent access to earlier interactions unless a user explicitly brings them back. A multi-cloud approach keeps several model families, including Anthropic, Llama, Mixtral and Google models, inside controlled environments, while calls to external APIs such as OpenAI are governed by agreements specifying near-zero retention and no training. Encryption in transit and at rest, role-based access controls, multi-factor authentication, vulnerability management and audit logging complete the picture. No European data residency option is announced.

Hosting countries
🇺🇸 United States
Watch-outs

Things to keep in mind

Risks and trade-offs to weigh before adopting Hatz AI.

  • Protected health information is forbidden on the platform: there is no HIPAA compliance and no Business Associate Agreement, and a well-meaning employee pasting patient details into a chat would breach that instruction without any technical barrier stopping them
  • All data is hosted in the United States, with Standard Contractual Clauses as the only safeguard for transfers out of the EEA, the United Kingdom and Switzerland
  • The terms of use reserve a perpetual right to aggregate and anonymise MSP Content in order to improve the platform, including its underlying machine learning models
  • Outputs come with no warranty of accuracy, completeness or truthfulness, and no guarantee that they are protectable or non-infringing; treating a generated document as verified fact is a real operational risk
  • No subprocessor list and no public data processing agreement are available, so a full third-party risk assessment cannot be completed from public information alone
  • After termination, MSP Content stays retrievable for only fifteen days, which is a short window for an organisation that has moved substantial knowledge work onto the platform
  • Making AI the default route for drafting, triage and analysis can quietly erode the in-house judgement that used to check the work, especially where credits, not review, are the limiting factor
Setup

Setup & Integrations

Technical difficulty

Low for the end user, moderate for the partner. There is nothing to install: the platform runs in a browser, and the MSP provisions the tenant and sends the invitations. Apps, workflows and agents are built in plain language through the Workshop Assistant, with no code required. Real administrative work sits with the partner, who activates connectors from the customer dashboard and, for something like ConnectWise Manage, must create a least-privilege security role first. Webhooks and API keys assume genuine technical skill, but most clients never touch them.

Deployment

Web appAPI

Integrations

Microsoft 365 Microsoft Teams Microsoft Excel OneDrive SharePoint Outlook ConnectWise Manage Halo PSA Pax8 ScalePad HubSpot Salesforce Klaviyo Brevo Apollo Hunter.io Go High Level Intercom Zapier Make N8n Slack Notion Asana Linear Monday Airtable Atlassian Webflow Calendly Cal.com Google Calendar Google Maps Gmail LinkedIn X Reddit Stripe Fireflies SerpApi Tavily Egnyte Pinecone Snowflake
Company

Behind Hatz AI

Company name
Hatz AI, Inc.
Founded
30/10/2023
Country of origin
🇺🇸 United States
UBO
INFORMATION_NOT_FOUND
UBO country
INFORMATION_NOT_FOUND
Domain registrar country
🇺🇸 United States
Support contact

Fundraising

Seed round of USD 2.5 million announced on 4 January 2024, led by Vestigo Ventures, with participation from Alex Weiss (ClearSky), Matt Higgins (RSE Ventures), Jim Brown (Long Ridge), Jon McNeill (DVx Ventures), Iqram Magdon-Ismail (Venmo co-founder) and Aidan Kehoe (Nadia Partners). Reported in a press release, not on the company website.
No later round is confirmed by a primary source; higher cumulative totals circulating on third-party funding trackers were not retained.

Social

Official links

Resources

All the official URLs gathered for verification and reference.

Compare

Alternatives

Tools that compete with or complement Hatz AI.

C ChatGPTM Microsoft Copilot Studio
FAQ

Frequently asked questions

Can I buy Hatz AI directly from the company?
No. The partnerships FAQ is explicit: to ensure the best possible experience, all Hatz customers are serviced through the partner network of managed service providers. If you are not a partner, Hatz will suggest partners who can get you started.
Does Hatz train AI models on my data?
No. The security page states a strict no-training policy on customer data, and the end customer terms add that Hatz's agreements with its LLM providers prohibit them from using or sharing End Customer Data to train their models. Providers may hold anonymised data briefly for abuse monitoring, then remove it.
Where is my data stored?
In AWS data centres in Virginia, in the United States. Conversation histories, user settings and organisational data are logically separated by tenant, organisation and user, and the inference layer is deliberately kept apart from stored history.
What security certifications does Hatz hold?
SOC 2 Type I and Type II, plus SOC 3. Reports are available to security-focused organisations on request at help@hatz.ai under a mutual non-disclosure agreement, or through the trust.hatz.ai portal. Independent firms also run regular penetration testing.
Is Hatz AI suitable for healthcare data?
No. A help centre article dated 23 July 2026 states that Hatz does not currently support HIPAA compliance and does not offer or enter into Business Associate Agreements, and instructs users not to process, store or transmit protected health information on the platform.
How much does it cost?
There is no public price. Pricing is set by the MSP partner that serves you, and partners are given custom pricing models and their own margins. Consumption itself is measured in Hatz Credits allocated monthly to your tenant.
What is a Hatz Credit?
A unit of AI usage. Each tenant receives a monthly credit allowance shared across its users, and the allowance resets at the start of every calendar month without carrying unused credits forward. A typical chat costs between 1 and 30 credits depending on the model, length and complexity.
How many AI models can I use?
More than 65 large language models, drawn from thirteen labs including Amazon, Anthropic, DeepSeek, Google, Meta, Mistral, NVIDIA, OpenAI, Qwen and xAI. Automatic model selection can choose one for you, and availability can vary by organisation, package and rollout status.
Does Hatz AI offer an API?
Yes. Users whose role includes the Create API Token permission can generate API keys that inherit their own account permissions, and a dedicated API reference is published at api-docs.hatz.ai. Workflows can also be run programmatically from external systems through HTTP webhooks.
Is there a mobile app?
None was found. Hatz AI is used through the web workspace at admin.hatz.ai, with programmatic access available through its API. No iOS app, Android app or browser extension is mentioned anywhere on the site or in the help centre.
Conclusion

Should you pick Hatz AI?

Hatz AI is a mature, unusually well-documented product rather than a thin landing page: the help centre alone runs to well over two hundred articles covering models, workflows, integrations, billing and support policy. Its differentiator is not raw model power, which it borrows from thirteen outside labs, but governance — tenant isolation, role-based access control, SOC 2 Type I and Type II with SOC 3, an unconditional no-training policy and credit allowances that cap what a team can spend before anyone notices.

The indirect distribution model is simultaneously the strongest and the most limiting thing about it. Going through a managed service provider means an SMB gets local hands-on setup, training and a human to call, which is exactly what most small companies lack when they try to adopt AI. It also means there is no way to try the product, no published price, no self-service sign-up, and a final cost that depends entirely on which partner you happen to work with. Two buyers may pay very different amounts for the same platform.

The compliance picture is solid at the base and thin at the edges. Encryption, MFA, audit logging, penetration testing and clear data ownership terms are all in place. But there is no public data processing agreement, no subprocessor list, no Article 27 EU representative, no HIPAA support and no BAA, and all hosting sits in Virginia with Standard Contractual Clauses as the only transfer safeguard for European data. The terms also reserve a perpetual right to aggregate and anonymise partner content for product improvement, which is worth reading closely.

It suits an English-speaking small or mid-sized business that already trusts an MSP and wants sanctioned AI quickly. It suits an organisation demanding EU data residency, healthcare compliance or transparent pricing far less well.