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Chatnode
✓ verifiedFreemium
Platform to build AI customer-service agents trained on your data that answer 24/7, take real actions and hand off to humans.
10K visits/mo44K saves
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Augment Code
✓ verifiedPaid
Agentic coding platform (Cosmos) that runs software-dev agents at org scale, using a codebase context engine to cut token cost.
544K visits/mo
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PromptLayer
✓ verifiedFree
Prompt engineering, management, and LLM observability platform.
212K visits/mo
Pricing
Free: $0/mo (35 credits/mo, 1 chatbot)
Lite: $35/mo (1,250 credits/mo, 1 agent)
Standard: $89/mo (12,500 credits/mo, 3 agents)
Scale: $377/mo (50,000 credits/mo, 8 agents)
Free trial available
Business: $100/mo flat (up to 50 seats, $100 usage included)
Free trial available
No public pricing
No public pricing
Core features
- ✦AI agents trained on website/docs with auto-retrain
- ✦AI Actions (Stripe billing, Calendly booking, API calls)
- ✦Multi-channel embed (site, Slack, Notion and more)
- ✦Human handoff with context
- ✦Analytics on deflection and satisfaction
- ✦Multiple LLMs selectable per task
- ✦Context Engine for codebase understanding
- ✦Agents across the full SDLC
- ✦Model routing / bring-your-own-keys
- ✦Automated code review and test coverage
- ✦CLI, MCP and native tool integrations
- ✦Enterprise security (SOC 2, ISO 42001, SSO)
- ✦Collection of MCP Servers
- ✦Search and discovery of MCP Servers
- ✦MCP Client directory
- ✦Community platform for sharing and learning about MCP Servers
- ✦Prompt management
- ✦Prompt evaluations
- ✦LLM observability
- ✦Team collaboration
- ✦Version control for prompts
- ✦A/B testing of prompts
- ✦Prompt Registry
- ✦Historical backtests
- ✦Regression tests
- ✦Usage monitoring
Use cases
- →Automate customer support
- →Book meetings and complete tasks in chat
- →Capture and qualify leads
- →Keep answers current via auto-retrain
- →Automating PR code review
- →Raising test coverage
- →Incident investigation and remediation
- →Large-scale migrations and onboarding
- →Enhancing AI capabilities by connecting to external data sources and tools
- →Integrating AI models with various services like databases, APIs, and file systems
- →Building AI applications that can access real-time information and perform actions
- →Connecting Claude to MCP servers to access external data sources and tools
- →Scaling customer support automation with LLMs
- →Empowering non-technical teams with prompt engineering
- →Building personalized AI interactions
- →Debugging LLM agents
- →Improving content creation processes
- →Managing and monitoring prompts with a team
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