GlassFlow® documentation

GlassFlow is the observability and context layer for teams running AI agents in production. Two products sit under the GlassFlow umbrella. Pick one to get started.

Rius

Agent observability

Trace every LLM call, tool invocation, and agent step. Monitor cost, tokens, and errors.

Built for long-running agents, with MCP in both directions and extended trace retention. Query every trace from your AI client, no dashboard required.

Explore Rius →

Tares

Context infrastructure

The context layer for your agents.

Instead of an agent calling each tool at runtime, Tares pre-processes and delivers exactly the data your agent needs, cutting token consumption and latency.

Explore Tares →