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AI super-assistant plus enterprise ML platform: ChatLLM for teams and end-to-end model building for enterprises; broad, pricing not shown.
Open-source platform to build, deploy and monitor agentic AI workflows and RAG apps, with cloud, self-host and enterprise options.
Open-source, self-hosted app to manage teams of AI agents like a company - org chart, goals, budgets and per-agent approvals.
Enterprise AI platform where marketing, sales, and support teams build governed AI agents on Writer's own Palmyra models.
No public pricing
No public pricing
No public pricing
Free trial available
- ✦ChatLLM access to multiple top AI models
- ✦AI agents and automation
- ✦No-code full-stack app creation
- ✦Enterprise generative AI platform
- ✦Structured ML model building
- ✦Optimization and forecasting
- ✦Visual workflow studio for agents
- ✦RAG knowledge pipelines
- ✦Agent runtime with tools and memory
- ✦Marketplace of models and plugins
- ✦Publish as app, API or MCP tool
- ✦Logging, analytics and monitoring
- ✦Manage teams of AI agents
- ✦Bring-your-own-agent (any runtime/provider)
- ✦Org chart with roles and reporting lines
- ✦Goal alignment for tasks
- ✦Per-agent budget and cost controls
- ✦Ticket system with full audit trail
- ✦WRITER Agent for delegating end-to-end tasks in natural language
- ✦Agent Playbooks for repeatable, on-brand workflows
- ✦AI Studio for building custom agents on company data
- ✦Knowledge Graph for grounding agents in company-specific context
- ✦Palmyra proprietary LLMs built for regulated enterprises
- ✦Enterprise security, identity, and compliance controls for IT
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents
- →Building AI agents and chatbots
- →Creating RAG-based knowledge apps
- →Deploying LLM apps at enterprise scale
- →Orchestrating agents across business functions
- →Running dev, marketing and research agents
- →Building autonomous-business workflows
- →Governing and budgeting agent work
- →Automating on-brand marketing content production at scale
- →Handling inbound customer support responses with AI agents
- →Building custom AI agents connected to a company's internal systems
- →Enforcing brand voice and terminology consistency across teams
- →Deploying AI under enterprise security and compliance requirements