We make it easy to run
AI agents on data
Deploy production-ready AI agents that can access your data in minutes, not months. No vector database setup, no infrastructure management.
How It Works
Three simple steps to deploy AI agents that understand your data
Connect Data
Upload or connect your internal datasets directly to our platform. No complex setup required.
Create Projects
Control your policies and use cases for each project. Set access controls and define agent behavior.
Ship
Let AI agents consume your data and provide intelligent responses. Deploy in production instantly.
Context-Aware AI Agents
We make your AI agents context-aware. Simply choose which data sources to connect; we will continuously index documents into a memory layer and generate context for your AI agent.
Context Engineering
Enrich your agent with real-time context from your data for all types of data sources. Our intelligent indexing system ensures your AI always has the most relevant information at hand.
Intelligent Memory Layer
Documents are automatically indexed and organized into a sophisticated memory layer that understands relationships, patterns, and context across all your connected data sources.
Why Choose Tropicalia
Data Sources
Tropicalia
API/MCP
Try It Yourself
Upload a PDF or TXT document and see how Tropicalia processes it
Sample Response 1:
Upload a document to see AI responses
Sample Response 2:
AI will analyze your content
Zero Infrastructure Management
No vector databases to set up, no servers to maintain. We handle all the complexity so you can focus on building AI agents.
RAG-as-a-service
Retrieval-Augmented Generation as a service. Get powerful RAG capabilities without managing the underlying infrastructure.
Deploy in Minutes
From data connection to production AI agents in under 10 minutes. No complex configurations or waiting periods.
Connect Any Data Source
Integrate with your existing infrastructure and tools seamlessly
Cloud Storage
Databases
AI Models
Tools
Frequently Asked Questions
Why does AI need data?
To unleash the potential of generative AI, it needs to be aware of the user's context and data: documents, emails, calendars, meeting transcripts, preferences, work streams, contacts, and more.
What is the alternative to using Tropicalia?
Traditionally, harnessing this data requires you to integrate with numerous data sources, build and scale an ETL pipeline to ingest that data, transform and clean the data, index, contextualize and store it, and spend countless hours fine-tuning chunking, embedding, metadata prompts, and much more. And that's before we even talk about security, prompt injections, and data leaks.
Do we store or sell data?
No. We don't. We do store summaries of that data and extracted information in our knowledge graph.