Enterprise Search & Knowledge Discovery Software Pricing 2026

Enterprise search indexes and makes searchable the content scattered across an organization's systems (documents, intranets, databases, apps), so employees can find information quickly from one search bar. Modern platforms add relevance tuning, personalization, and increasingly AI-driven semantic search and answers, respecting access permissions.

Enterprise search is typically priced by query volume, indexed documents/records, or users, with open-source options (Elastic) free to self-host and managed/SaaS platforms charging usage-based or custom enterprise pricing. Costs scale with data volume, query traffic, and connectors. Implementation and relevance tuning add to total cost.

Open-source engines like Elastic avoid license fees but require engineering to deploy, scale, and tune. Managed and SaaS platforms (Coveo, Algolia, Lucidworks) charge usage fees but offload operations and provide built-in relevance and connectors. Self-hosting is cheaper in license terms; managed often wins once engineering time is counted.

Watch for pricing that scales with indexed documents and query volume, per-connector fees, infrastructure and scaling costs for self-hosted clusters, and the relevance-tuning effort to make results useful. Adding AI semantic search and generated answers introduces LLM token costs on top.