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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.
Enterprise AI observability and security platform to monitor, evaluate, and govern agentic and ML systems with guardrails.
Open-source LLMOps platform uniting prompt management, evaluation and observability for teams shipping reliable LLM apps.
General AI agent executing tasks and integrating thousands of apps; very high traffic.
Open-source platform to build, deploy and monitor agentic AI workflows and RAG apps, with cloud, self-host and enterprise options.
No public pricing
No public pricing
No public pricing
- ✦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
- ✦End-to-end agentic and ML observability
- ✦Real-time guardrails (hallucination, PII, jailbreak)
- ✦Continuous evaluations and custom judges
- ✦Root-cause analysis and decision lineage
- ✦AI governance, risk, and compliance controls
- ✦Flexible SaaS, VPC, or on-prem deployment
- ✦Prompt management as a single source of truth
- ✦Playground for prompt experimentation
- ✦Evaluation to measure changes before production
- ✦Observability and tracing for debugging
- ✦Collaboration across technical and non-technical roles
- ✦Open-source and self-hostable
- ✦Create presentations, websites, reports, slides, documents, podcasts images & videos
- ✦Conduct deep research on any topic
- ✦Command a virtual computer to browse the web
- ✦Connect and automate with over 2700+ apps
- ✦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
- →Chat with many AI models in one place
- →Build and deploy ML models
- →Automate tasks with AI agents
- →Monitoring production AI agents
- →Enforcing safety guardrails on LLM apps
- →Evaluating and debugging model behavior
- →Governance and compliance for enterprise AI
- →Version and manage prompts centrally
- →Benchmark and evaluate LLM outputs
- →Debug and trace production LLM issues
- →Collaborate across a team on LLM apps
- →Generate a high-conversion landing page for a startup's ebook.
- →Build a web-based image cropper tool with live preview.
- →Create a beginner-friendly PDF cheatsheet for Python.
- →Develop a one-week travel itinerary for a destination like Vietnam.
- →Analyze social media mentions and sentiment for a specific entity.
- →Organize hiring task submissions from emails into a Google Sheets spreadsheet.
- →Clone a pixel-perfect website for design accuracy and responsive web experience.
- →Make a podcast on the rise of SpaceX, make it conversational and include fun facts.
- →Building AI agents and chatbots
- →Creating RAG-based knowledge apps
- →Deploying LLM apps at enterprise scale