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pipeshub-ai

by pipeshub-ai

Workplace AI platform for explainable multi-agent workflows

Python
Updated Feb 11, 2026
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What It Does

Orchestrates workplace AI workflows for enterprise search and automation. Provides an extensible, explainable platform that connects connectors (notion, gmail, drive, slack) with agent chains and RAG pipelines to build repeatable automations. Includes tooling for inspection and explainability so teams can trace how results were produced and which agents contributed to an outcome. This architecture can leverage the Model Context Protocol (MCP) to coordinate context across agents, and aligns with established patterns like the Agent Registry Pattern for managing agents.

Why It Matters

As organizations adopt agent-based automations, understanding who did what and why becomes essential for trust and governance. PipesHub surfaces provenance and explanation for agent actions, making it easier to evaluate agent reliability and uncover failure modes before they reach users. That explainability combined with built-in connectors helps teams treat agent behavior and track records as first-class operational data, often enhanced by a Human-in-the-Loop approach to oversight.

Best For

Engineering teams building enterprise RAG and automation flows that need connectors, explainability, and operational visibility. Consider adopting a Planning Pattern to organize workflows and a Agent Registry Pattern for scalable agent management.

Applications

  • Connect enterprise sources (notion, gmail, drive) into RAG pipelines for searchable knowledge workflows
  • Compose and debug agent chains with explainability to diagnose multi-agent failures
  • Automate workplace tasks (emails, Slack actions, doc updates) while tracing agent provenance
Works With
langchainlanggraphnotiongmailslackollamaperplexityllamaparsedriveglean
Topics
agentagentsaidrivegleangmailknowledge-graphlangchainlanggraphllamaparse+6 more
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Keywords
multi-agent orchestrationagent delegationexplainabilityrag