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All-in-one no-code platform combining forms, workflow automation, AI agents, a database and email in a single subscription.
Free AI helper that turns a plain-English description of a task into the matching Git command to copy and run.
Low-code platform combining AI form building with BPMN/DMN workflows and approvals for teams automating data-heavy processes.
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
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 Git command suggestions
- ✦AI-driven command matching
- ✦Copy-ready command output
- ✦Git guides and reference
- ✦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)
- ✦AI-assisted and drag-and-drop form builder
- ✦BPMN/DMN visual workflows and decision rules
- ✦Automated routing and multi-step approvals
- ✦Role-based access control, SSO/SAML
- ✦Webhooks, REST API and app connectors
- ✦Public cloud, private cloud or self-hosted deployment
- ✦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
- →Find the correct Git command quickly
- →Learn Git syntax by describing a goal
- →Avoid memorizing Git flags
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Automating submission-to-approval workflows
- →Digitizing government and public-sector forms
- →Managing compliance-heavy processes in finance/healthcare
- →Standardizing internal request and review flows
- →Unifying fragmented enterprise data
- →Governing data for AI workloads
- →Moving AI pilots to production
- →Powering analytics with trusted data