
ZivyAI assistant that prioritizes and organizes Slack messages for engineering and product teams.
Overview
Key features
- AI-driven message prioritization
- Automatic categorization of conversations
- Mention and thread summarization
- Context-aware filtering
- Slack-native integration
- Personalized relevance learning
Pricing
- Model
- Freemium
- Category
- Workflow automation
- Rating
- 4.8 / 5 (4)
Use cases
Cut through Slack noise for engineers
Engineering teams use Zivy to filter out low-priority chatter and surface critical messages, reducing distractions during deep work and focus time.
Prioritize mentions and decisions
Product managers quickly catch up on key mentions, decisions, and action items across multiple channels without manually scanning every thread.
Streamline async collaboration
Distributed teams rely on Zivy to organize conversations into actionable groups, making asynchronous communication more efficient across time zones.
Personalized Slack triage
Individual contributors let Zivy learn their context and behavior to automatically categorize incoming messages by relevance and urgency.
Pros & Cons
Pros
- Reduces Slack overload with smart prioritization
- Tailored for engineering and product team workflows
- Surfaces important mentions and decisions quickly
- Integrates directly with existing Slack setup
Cons
- Limited to Slack-based communication
- Effectiveness depends on training period and usage patterns
- May not fit teams using other chat platforms
Battle record
Across 6 battles in the Pantheon.
Last 5 battles
- #4
Workflow automation Showdown — July 9, 2026
Jul 9, 2026 · #4 of 5
- #4
Workflow automation Showdown — December 24, 2025
Dec 24, 2025 · #4 of 5
- #4
Workflow automation Showdown — September 5, 2025
Sep 5, 2025 · #4 of 5
- #4
Workflow automation Showdown — July 25, 2025
Jul 25, 2025 · #4 of 5
- #1
Workflow automation Showdown — July 16, 2025
Jul 16, 2025 · #1 of 4
Reviews
Average from 4 ratings.
Sign in to leave a review.
Years in this space
I've evaluated a lot of these over the years. What stands out here is mention and thread summarization — handled better than most — and tailored for engineering and product team workflows. Effectiveness depends on training period and usage patterns is my one real gripe. Worth the time if this is your use case.
Years in this space
I've evaluated a lot of these over the years. What stands out here is context-aware filtering — handled better than most — and integrates directly with existing Slack setup. May not fit teams using other chat platforms is my one real gripe. Worth the time if this is your use case.
Solid for our team
We rolled this out across the team last quarter and integrates directly with existing Slack setup. AI-driven message prioritization fits neatly into how we already work, and automatic categorization of conversations removed a step we used to do by hand. but it has held up under daily use.
Years in this space
I've evaluated a lot of these over the years. What stands out here is context-aware filtering — handled better than most — and tailored for engineering and product team workflows. Worth the time if this is your use case.
Q&A
Is there a learning period for Zivy to become effective, and what factors affect its accuracy?
Yes, Zivy’s relevance improves as it learns from individual usage patterns and role context; its effectiveness depends on the amount of interaction and the consistency of team communication habits during the training phase.
Asked by Zain Malik · Aug 31, 2025
What integrations does Zivy require and can it work with non‑Slack tools?
Zivy integrates directly with Slack as a native app, processing all channel and thread activity within your existing workspace; it does not support other chat platforms, so its functionality is limited to Slack‑based communication.
Asked by Hasan Demir · Aug 10, 2025
How does Zivy prioritize Slack messages for engineering and product teams?
Zivy uses AI to analyze messages, channels, and threads, then groups them into categories like "needs your input," "good to know," and "everything else," highlighting mentions and decisions based on each user’s behavior and context.
Asked by Rania Nasser · Jul 9, 2025
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