Fluideosolutions is sharing a quick look at ContextIQ, an AI context engineering suite from Trango Compute. If you build LLM and agent systems, you already know that “the model works” isn’t the same as “the system works reliably.” ContextIQ helps bridge that gap by turning context architecture decisions into clear, visual diagrams—so teams can reason about retrieval, memory, and token allocation without relying on prose or dense code.
Key ContextIQ tools for everyday debugging
ContextIQ includes the RAG Chunk Inspector to see how documents split into chunks, the Agent Workflow Visualizer for LangGraph and other frameworks, and the Agent Trace Inspector to review OTLP-style traces with per-node token attribution.
From memory design to exports
For deeper system planning, the Memory Architecture Visualizer maps memory layers as a DAG with token budgets, while the Token Inspector helps compare model token counts and costs. ContextIQ also supports one-click exports (including PDF) and keeps diagrams private.
Source: https://contextiq.trango-compute.com/
That’s ContextIQ by Trango Compute, and it’s a practical way to engineer AI context more confidently.