Hebbia vs Viglet Turing ES

Hebbia has no write-up on Specifiction yet; its figures are above.

Viglet Turing ES is a self-hosted enterprise search platform that combines semantic navigation, content integrations and generative AI. Its search tools include faceted search, autocomplete, spotlights, targeting rules, result ranking and per-site AI insights. For AI workflows, it supports retrieval-augmented generation over indexed content, LLM instances, agents, tool calling and MCP server integration. Search backends include Apache Solr, Apache Lucene and Elasticsearch. Documented content integrations include Adobe AEM and web crawlers, plus Dumont DEP connectors for databases, file systems and WordPress. The listed LLM provider types include OpenAI, Anthropic, Gemini, Ollama, Amazon Bedrock, Cohere, Mistral and Vertex AI. It offers native sessions, OAuth2 social login and Keycloak single sign-on. Deployment options include Docker, a standalone JAR, source builds, Docker Compose and Kubernetes; it requires Java 21. The free plan costs nothing, and the product is documented as open source under Apache 2.0. The embedded-H2 setup is for local development and evaluation, not production.