We build production AI agents that integrate into your product or business workflow. Not prototypes, not demos — working systems that handle real tasks, call real tools, and run in production.
What we build:
Custom AI agents using OpenAI, Claude, and Gemini APIs. Tool-calling agents that interact with your existing systems. MCP (Model Context Protocol) integrations for connecting AI to your data sources. RAG pipelines for knowledge-grounded responses. Multi-step workflows with function calling, structured outputs, and error handling.
Our stack:
Next.js, TypeScript, Supabase, Vercel, AI SDK, OpenAI, Claude, Gemini, MCP, LangChain. We handle the full pipeline: prompt architecture, tool definitions, vector search, streaming responses, and deployment.
How it works:
We start with your use case and map the agent architecture. Then we build, test, and deploy the agent with proper error handling, logging, and monitoring. You get a production system, not a notebook.
Who this is for:
Founders building AI-native products. Teams adding AI capabilities to existing SaaS. Companies automating internal workflows with intelligent agents. Anyone who needs an AI system that actually works in production.
We build production AI agents that integrate into your product or business workflow. Not prototypes, not demos — working systems that handle real tasks, call real tools, and run in production.
What we build:
Custom AI agents using OpenAI, Claude, and Gemini APIs. Tool-calling agents that interact with your existing systems. MCP (Model Context Protocol) integrations for connecting AI to your data sources. RAG pipelines for knowledge-grounded responses. Multi-step workflows with function calling, structured outputs, and error handling.
Our stack:
Next.js, TypeScript, Supabase, Vercel, AI SDK, OpenAI, Claude, Gemini, MCP, LangChain. We handle the full pipeline: prompt architecture, tool definitions, vector search, streaming responses, and deployment.
How it works:
We start with your use case and map the agent architecture. Then we build, test, and deploy the agent with proper error handling, logging, and monitoring. You get a production system, not a notebook.
Who this is for:
Founders building AI-native products. Teams adding AI capabilities to existing SaaS. Companies automating internal workflows with intelligent agents. Anyone who needs an AI system that actually works in production.