Lamatic AI

Lamatic AI is an AI middleware platform that helps product teams build, deploy, and optimize AI agents without managing underlying infrastructure. It combines a visual flow builder, serverless edge deployment, and built-in observability tools to accelerate development of agentic applications for startups, agencies, and enterprise teams.

Key Features

• Visual Flow Builder: A no-code and low-code interface for building AI agents, automations, and processes using drag-and-drop nodes. Supports 300+ AI models including text, image, multimodal, and embedding models from providers such as OpenAI, Anthropic, Google, and open-source alternatives.
• Serverless Edge Deployment: Deploy AI agents and flows on edge infrastructure that scales automatically to handle millions of requests. Includes request caching, environment management, version control, and scheduled job execution.
• Agent Framework: Create and configure AI agents across multiple types including text agents, JSON agents, multimodal agents, and supervisor agents that coordinate sub-agents. Each agent can be configured with custom system prompts, tools, and model selections.
• Pre-built Templates: Ready-to-use templates for common patterns such as RAG chatbot, semantic search, website indexation, Slack bot, Google Drive indexation, and S3 indexation. Templates provide a starting point that teams can customize for their specific use cases.
• Integrations: Connect with 100+ tools, data sources, and apps through managed integrations, REST and GraphQL APIs, webhooks, and embeddable widgets. SDK support for JavaScript, TypeScript, React, Next.js, Python, and Go.
• Memory and Context: Built-in vector database and memory store for adding custom context to flows and agents. Supports document chunking, hybrid search, vector search, and keyword search operations to ground AI responses in proprietary data.
• Monitoring and Observability: Real-time request logs and traces, performance dashboards, reports with intuitive charts, and Langfuse integration for detailed LLM observability and cost analysis.
• Development Tools: Integrated development environment with a prompt IDE for testing prompts, a code IDE for JavaScript, and a GraphQL IDE for API requests. Built-in testing tools for flows, prompts, and code with full debugging capabilities.

Use Cases

• AI Chatbots and Assistants: Build conversational agents that answer questions using company data through RAG-based retrieval, deployable via embeddable chat widgets, Slack integration, or custom API endpoints.
• Automated Workflows: Create multi-step AI workflows that automate data extraction, content classification, document processing, and decision-making processes with branching logic and conditional execution.
• Knowledge Retrieval: Index and vectorize content from Google Drive, Amazon S3, websites, or uploaded documents, then enable natural language search and question answering over the indexed data.
• Semantic Search: Build search widgets that retrieve relevant information from vector databases using semantic understanding, providing more accurate results than traditional keyword matching.

Pricing

Lamatic AI offers a free Starter tier with 3,000 monthly requests and three requests per second. Paid tiers include Pro at $99 per month with 100,000 requests and Team at $149 per month with 100,000 requests and unlimited team members. Enterprise plans are available with custom pricing, on-premise deployment, SSO, and dedicated support.