Deploy Skald in your infra and have a private context layer for your AI agents and knowledge systems.
await skald.chat("What is our refund policy?")"Our refund policy allows returns within 30 days of purchase. Contact support@company.com to initiate a refund."
Skald saves you from having to create a new team just to manage RAG infrastructure. We do the dirty work and give you full customization.
The Skald context layer sits between your data sources and your AI applications, providing intelligent retrieval, memory, and knowledge management as a unified service.
Instead of each application managing its own RAG pipeline, the context layer provides a single source of truth for all your organizational knowledge.
Connect any LLM—OpenAI, Anthropic, open-source models, or your own. The context layer handles retrieval; you choose the generation.
Embedding generation, vector storage, reranking, caching, and scaling handled for you. Focus on your application, not the plumbing.
LLMs are powerful, but they don't know your data. The context layer automatically finds and delivers the right information from your sources, making every AI response is grounded in your actual knowledge.
A single API call connects your applications to your entire context layer. Ship today with confidence it will grow with your organization.
import { Skald } from '@skald-labs/skald-node';
const skald = new Skald('your-api-key-here');
// Create a memo
const result = await skald.createMemo({
title: 'Meeting Notes',
content: 'Full content of the memo...'
});
// Chat with the memo
const result = await skald.chat({
query: 'What were the main points discussed in the Q1 meeting?',
rag_config: {
references: { enabled: true },
reranking: { enabled: true, topK: 10 }
}
});
Platform
Ingest any document format with automatic extraction of text, tables, and structural elements.
Every response includes traceable references to original documents for complete auditability.
Choose your preferred foundation model or run inference entirely on your own infrastructure.
Deploy in your cloud or on-premises with complete data sovereignty and compliance controls.
Push context and get chat out-of-the-box so you can go live today. Then tune to your needs, experiment with different configs, and evaluate performance.
Python, Node.js, PHP, Go, C#, and Ruby SDKs ready for production use with full type support and comprehensive documentation.
Fine-tune reranking, vector search, system prompts, and retrieval strategies to meet your specific requirements.
Connect your agents to Skald using our official MCP server for seamless integration with AI assistants and development tools.
Unified context layer combining knowledge base, conversational memory, and institutional data for true organizational intelligence.
Experiment with different configurations and evaluate performance from inside Skald with built-in metrics and analytics.
See how leading enterprises are deploying secure, compliant context layers for their AI initiatives.