NaLU AI.dev
NaLU AI extracts real data from agent/user dialogues. Name, email, postal code, yes/no and more. From $0.0012 per validation.
NaLU AI extracts real data from agent/user dialogues. Name, email, postal code, yes/no and more. From $0.0012 per validation.
This page is designed to help you find out whether NaLU AI.dev is good and if it is the right choice for you.
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Semantic Dialog Extraction
Extracts clean values (names, CPFs, CEPs) from raw conversational dialogs, ignoring greetings or extra noise.
13+ Pre-built AI Validators
Ready-to-use, multi-layered AI validation for CPF, CNPJ, email, Brazilian license plates, and postal codes.
validate_reply Context Analysis
Understands complex chat context, detecting counter-proposals, indirect replies, and handoffs.
MCP Server & REST API
Integrate in 30 seconds via standard REST API or natively as an MCP server with Claude Code, Cursor, n8n, and Make.
Chatbot developers, AI engineers, CRM integrators, and automation specialists using platforms like n8n, Make.com, Claude Code, and Cursor who want to build resilient, production-ready conversational agents that capture lead data reliably.
NaLU AI is built specifically to address the "greetings vs data" problem in chatbot conversations. Instead of generic LLM processing or rigid regex, it uses multi-layered semantic extraction to isolate clean, structured data (like CPF, CEP, CNPJ, names, and emails) directly from raw user utterances, ignoring conversational noise.
Traditional solutions require you to prompt large language models directly (which is slow, expensive, and prone to hallucinations) or use complex regex (which breaks with basic typos or natural phrasing). NaLU AI offers 13+ specialized, pre-configured validators that operate in milliseconds for a fraction of the cost—starting at just 0.001(R 0,0058) per validation.
We got tired of building chatbots that saved conversational noise as lead data—like saving "Good morning! My name is John" with the name field literally containing "Good morning". Traditional regex failed constantly, and calling raw LLMs for simple validations was too slow and expensive. We built NaLU AI to be the missing NLU (Natural Language Understanding) validation layer for modern conversational agents.
NaLU AI is built using high-performance API architectures, advanced natural language processing (NLP) models, semantic embedding layers, and is accessible via a high-speed REST API and native Model Context Protocol (MCP) servers.
Fintechs automating customer onboarding and KYC validation E-commerce brands capturing shipping addresses and CEPs through WhatsApp B2B Lead generation agencies using AI sales agents to qualify prospects Customer support platforms routing hot leads and urgent human handoffs
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