ARIA
In oil & gas, manufacturing, retail, and most traditional industries, the most valuable operational knowledge isn't in any database — it lives in people's heads.
Core trick
Sends missing-context questions to humans over email or SMS, then resumes the same agent session when the reply webhook arrives.
Description
In oil & gas, manufacturing, retail, and most traditional industries, the most valuable operational knowledge isn't in any database
— it lives in people's heads. The engineer who remembers why a pump failed in 2019. The technician who modified a valve and never
updated the CMMS. You can't reach that knowledge with an MCP server, and you can't RAG your way to it. You have to ask, then wait —
sometimes for days.
ARIA is a human-in-the-loop agent platform that treats people as a first-class data source alongside tools and skills. When the
agent hits the boundary of what any system can tell it, it reaches out directly — over email, phone, SMS, Slack, or Zoom transcripts
— to the right human, waits however long it takes, integrates the response, and continues. Every inbound message routes back to the
same managed agent session via webhook, so the agent picks up exactly where it left off, days later if needed.
The first deployment targets oil & gas FMEA/RCM analysis. ARIA fans out three parallel specialist sub-agents (rotating equipment,
static, instrumentation), identifies missing context, batches questions to the analyst pool, escalates up the hierarchy if no one
replies, falls back to a phone call when needed, and produces a 4-sheet regulatory-grade Excel report. A process that takes a
reliability team three weeks now runs overnight.
The same architecture generalises to any industry where institutional knowledge is distributed across people rather than systems.
README excerpt
# ARIA — Autonomous Reliability Intelligence Agent > *Give an agent access to traditional tools — MCP servers, databases, a bash terminal. Then extend it one step further: let it reach out to real people, gather context from them directly, and complete the task entirely on its own. That's ARIA.* ## Demo [](https://www.youtube.com/watch?v=7M7cCDToC8o) ▶ [Watch on YouTube](https://www.youtube.com/watch?v=7M7cCDToC8o) ## The Core Concept Every capable agent today gets access to the same two things: **tools** (MCP servers, databases, APIs, a bash terminal) and **skills** (code execution, file generation, search). These let an agent act on structured, accessible data. ARIA extends this with a third layer: **people**. When the agent hits the boundary of what any tool or system can provide — because the context doesn't exist in any database, because the knowledge lives in someone's head — it reaches out directly. It emails, calls, or messages the right human, waits for a response, integrates what it learns, and continues. No human has to interact with any UI. No system has to be updated. The agent adapts to how people already communicate. The result is an agent that can complete long-running, real-world tasks entirely on its own — not because it has access to better data, but because it knows how to go get context that was never in any system. --- In oil & gas, manufacturing, retail, constructio