Spark Engine uses advanced AI models to transform text data into high-dimensional vector embeddings, allowing searches to go beyond keyword matching. When a user submits a query, Spark Engine processes it through natural language understanding to capture intent, compares it with indexed document embeddings, and ranks results by semantic similarity. The platform supports filtering, faceting, typo tolerance, and result personalization. With options for customizable relevance weights and analytics dashboards, teams can monitor search performance and refine parameters. Infrastructure is fully managed and horizontally scalable, ensuring low-latency responses under high load. Spark Engine's RESTful API and SDKs for multiple languages make integration straightforward, empowering developers to embed intelligent search into web, mobile, and desktop applications rapidly.

OpenKBS connects to your knowledge sources—PDFs, Google Drive, Notion, Slack, websites—and indexes them using advanced NLP. It then provides an AI chat agent accessible via web or embeddable widget. The agent understands user questions, retrieves relevant information, and delivers concise answers. Admins can customize appearance, configure update schedules, and monitor usage through analytics dashboards. This seamless integration streamlines support, onboarding, and documentation search across your organization.