Release notes

This page lists notable changes to Foundation4 since February 2026, newest first. Each heading names the month in which the changes under the heading were completed in the code.

September 2026

Full-text search. Pipelines can be searched by keyword as well as by meaning. A pipeline created with has_full_text_search: true accepts search requests with type: "search". Foundation4 uses PostgreSQL text search, detects the language of each fragment and each query automatically across 17 languages, matches all of the query terms, and ranks results by relevance. Full-text search applies classifications and metadata filters in the same way as vector search.

For hybrid results, the client application runs a vector search and a full-text search and fuses the two result lists. Native hybrid search with re-ranking inside Foundation4 is planned.

Full-text search must be enabled when a pipeline is created. A full-text search request against a pipeline without full-text search enabled returns HTTP 501.

OpenTelemetry export. The API server exports a span for each API request, with the request identifier, and the log records of the API server through the OpenTelemetry Protocol (OTLP) when the environment of the API server sets an OTLP endpoint. The workers, the gRPC service and the dashboard export no OpenTelemetry data. Observability describes the export.

March 2026

MCP endpoint. AI assistants that support the Model Context Protocol (MCP) can connect to /mcp over streamable HTTP, using the same API key headers as the REST API. Three read-only tools are available: list pipelines, list the classifications of a pipeline, and search a pipeline. In the current release, MCP clients connect through a port forward to the API server.

Verified database TLS. Connections to PostgreSQL can verify the server against a custom certificate authority.

Document processing metrics. The workers publish the time spent splitting text and computing embeddings as separate Prometheus metrics, next to the total processing time.

February 2026

OpenAI-compatible chat completions endpoint. POST /openai/v1/chat/completions relays requests to a registered LLM, selected with the x-llm-id header, so that tools built on OpenAI SDKs can use models registered in Foundation4.

Embedding test endpoint. POST /embedding-models/{id}/query returns the embedding for a piece of text, which confirms that a model is configured correctly.

Branding. The product name shown in the API documentation and in the start log line of the API server can be set at installation, with the configuration key branding.name.

License limits. The API server checks the object limits of the license before each operation that creates or changes data.