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Glean
✓ verifiedFreemium
Enterprise work-AI platform for knowledge discovery and automation.
👁 3.2M/mo
Pricing
Essential: $29 per seat/mo (billed annually) + $0.99 per Fin resolution
Advanced: $85 per seat/mo (billed annually) + $0.99 per Fin resolution
Expert: $132 per seat/mo (billed annually) + $0.99 per Fin resolution
Fin AI Agent (on existing helpdesk): $0.99 per Fin resolution (50 resolutions per month minimum)
Copilot: $29 per agent/mo (billed annually)
Proactive Support Plus: $99 /mo
No public pricing
Free Plan: $0 one-time
Hobby: $16/month
Standard: $83/month
Growth: $333/month
Auto Recharge Credits: $11/mo for 1000 credits
Credit Pack: $9/mo for 1000 credits
Enterprise Plan: Contact for Pricing
No public pricing
Core features
- ✦Fin AI Agent for automated customer support
- ✦Omnichannel support (inbox, tickets, phone, help center)
- ✦AI-enhanced inbox for agent productivity
- ✦AI Insights & Reporting for performance optimization
- ✦Workflow automation with a visual builder
- ✦Work AI Platform
- ✦Glean Assistant (AI assistant)
- ✦Glean Agents (AI agent builder)
- ✦Glean Search (Enterprise search)
- ✦Connectors (Data integration)
- ✦Data & AI Governance
- ✦Security
- ✦Web scraping
- ✦Web crawling
- ✦Data extraction in Markdown, JSON, and screenshot formats
- ✦Dynamic content handling
- ✦Rotating proxies
- ✦Rate limits management
- ✦Open-source availability
- ✦Media Parsing
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
Use cases
- →Providing instant customer service with Fin AI Agent
- →Managing customer inquiries across multiple channels
- →Automating support workflows to improve efficiency
- →Empowering support agents with AI-powered tools
- →Gaining insights into customer service performance
- →Finding information across various company apps
- →Creating and summarizing content
- →Automating repetitive tasks and workflows
- →Onboarding new employees and projects
- →Improving customer service with quick access to knowledge
- →Enhancing engineering productivity
- →Streamlining sales processes
- →Powering AI assistants with real-time web content
- →Enhancing sales data with web information
- →Adding scraping capabilities to code editors
- →Enabling customers to build AI apps with web data
- →Extracting comprehensive information for in-depth research
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
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