VectorAdmin provides a comprehensive interface to handle all aspects of vector database management. Users can integrate multiple vector store providers through API keys, view and filter vector collections, track ingestion statuses, and monitor query latencies. The platform supports bulk import of vector data via CSV or JSON, customizable similarity search parameters, and visual embeddings distribution. Administrators gain insights into index performance with dashboards showing CPU, memory, and storage metrics. Additionally, VectorAdmin features user roles with granular permissions, alerting on threshold breaches, and audit logs for compliance, simplifying deployment of AI-driven search and recommendation systems.

Cognita offers a modular architecture for building RAG applications: ingest and index documents, select from OpenAI, TrueFoundry or third-party embeddings, and configure retrieval pipelines via YAML or Python DSL. Its integrated frontend UI lets you test queries, tune retrieval parameters, and visualize vector similarity. Once validated, Cognita provides deployment templates for Kubernetes and serverless environments, enabling you to scale knowledge-driven AI assistants in production with observability and security.