# Hai vs. Gemini

Canonical: https://usehai.ai/compare/gemini

Markdown: /compare/gemini.md

Description: Gemini is useful inside a productivity ecosystem. Hai is built for mixed company stacks where work crosses chat, CRM, finance, support, files, and custom systems.

Page: Hai vs. Gemini comparison.

For: Teams comparing Hai with Gemini.

Hai can: Hai is designed as the connective workspace across the tools a company already runs, including Slack, Teams, CRM, finance, support, email, calendar, and files.

Gemini is useful inside a productivity ecosystem. Hai is built for mixed company stacks where work crosses chat, CRM, finance, support, files, and custom systems.

## Summary

- **Hai:** Hai is designed as the connective workspace across the tools a company already runs, including Slack, Teams, CRM, finance, support, email, calendar, and files.
- **Gemini:** Gemini is a capable assistant for Google-centric productivity, search, writing, analysis, and collaboration workflows.

## Comparison

- **What it is**
Hai: A shared AI workspace where company context, channels, tools, live artifacts, tasks, and governed actions stay together.
Gemini: A frontier assistant for individual prompting, writing, analysis, coding, and open-ended reasoning in a separate chat surface.
Takeaway: Hai is built around company execution. The other tool is strongest as a flexible thinking partner.
- **Where work happens**
Hai: Hai starts in Slack, Microsoft Teams, and the web app, then keeps the work attached to shared threads, tasks, and artifacts.
Gemini: Most work happens in a standalone chat or document surface, then gets copied back into the systems where the team operates.
Takeaway: Hai reduces the gap between asking for work and moving that work through the business.
- **Business systems**
Hai: Hai is designed for governed access to CRM, finance, support, files, calendar, email, ATS, and internal systems.
Gemini: Connections are useful for lightweight retrieval and personal workflows, but business-tool access is not the center of the product.
Takeaway: Hai is for cross-system work where context and action both matter.
- **Outputs**
Hai: Hai can return the right surface for the work: a booking, candidate scorecard, support triage queue, live revenue widget, task board, or drafted outreach sequence.
Gemini: The default output is a response, document, or generated file that still needs to be moved into the operating workflow.
Takeaway: Hai focuses on finished work, not only answers.
- **Team memory**
Hai: Hai is built around shared company memory: files, notes, meetings, channels, artifacts, and recurring decisions become reusable context.
Gemini: Memory is usually personal or conversation-scoped, which makes repeated team workflows harder to compound over time.
Takeaway: Hai is intended to get more useful as the company keeps working inside it.
- **Recurring work**
Hai: Hai supports scheduled checks, heartbeat-style monitoring, triggered tasks, and proactive suggestions for repeated business workflows.
Gemini: The user usually has to start the conversation, restate the context, and manually move the result forward.
Takeaway: Hai can be present before someone remembers to ask.
- **Governance**
Hai: Hai is designed for permission-scoped integrations, reviewable actions, audit trails, and enterprise security conversations from the start.
Gemini: Enterprise controls may exist, but the core pattern remains a broad assistant used by individuals or teams.
Takeaway: Hai treats access, scope, and accountability as part of the workflow design.

## Choose Hai When

- You need AI inside Slack, Teams, tasks, and shared workspace artifacts.
- Work depends on company systems such as CRM, finance, support, ATS, email, calendar, and files.
- Outputs should become bookings, scorecards, queues, widgets, tasks, or outreach, not just text.
- You want scheduled, triggered, or proactive work with clear access boundaries.

## Choose Gemini When

- You need a general-purpose assistant for one-off questions, writing, brainstorming, or coding.
- You work mostly solo and can manually provide the context each time.
- You do not need governed read/write access across company systems.