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All-in-one no-code platform combining forms, workflow automation, AI agents, a database and email in a single subscription.
Google's cloud-based, AI-assisted development environment, now rebranded and merged into Firebase Studio.
Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
IBM's open, hybrid data lakehouse that connects, governs and optimizes enterprise data to make it AI-ready across clouds and on-premises.
No public pricing
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
- ✦Drag-and-drop form builder with conditional logic
- ✦Workflow automation with 60+ node types and 400+ integrations
- ✦Prebuilt and custom AI agents for tasks like lead scoring
- ✦Relational database with AI-enriched columns
- ✦Drag-and-drop email builder with AI-drafted content
- ✦Company and contact enrichment and web research tools
- ✦Natural language to SQL conversion
- ✦Cloud-based IDE accessible from the browser
- ✦AI-assisted coding
- ✦Cross-platform app development
- ✦Preconfigured workspaces and templates
- ✦Now part of Firebase Studio
- ✦Multi-agent collaboration for end-to-end tasks
- ✦Persistent memory and custom rules
- ✦Extensible skills and plugins
- ✦Rich context across code, images, and directories
- ✦Automatic codebase documentation generation
- ✦Terminal-native CLI and JetBrains IDE plugin
- ✦Cloud-hosted agents for enterprise use
- ✦Open hybrid data lakehouse
- ✦Connects data across clouds and on-prem
- ✦Governance, lineage and access controls
- ✦Business-context enrichment
- ✦AI-ready data for analytics and models
- →Capturing and automatically routing sales leads
- →Building onboarding or support-triage workflows
- →Running AI-driven lead scoring and qualification
- →Sending personalized, data-merged email campaigns
- →Generating SQL queries from text descriptions.
- →Building apps from anywhere in the browser
- →Prototyping with AI assistance
- →Developing cross-platform applications
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Unifying fragmented enterprise data
- →Governing data for AI workloads
- →Moving AI pilots to production
- →Powering analytics with trusted data