Introduction

During our hackathon, Manoj Batra delivered a focused, production-minded prototype that brings clarity to UiPath Orchestrator job status across folders. His Innovative UiPath Orchestrator Monitoring solution fetches folder-level job statistics, surfaces running and recent faulted jobs, enriches those findings with logs and error context, and uses an LLM to generate concise, human-readable summaries. The result is a polished HTML briefing delivered straight to Outlook — turning noisy job telemetry into proactive, readable intelligence that ops teams and stakeholders can act on immediately.

The Challenge

Enterprise RPA sprawl creates a lot of telemetry, but not all of it is signal. Orchestrator exposes per-job and per-folder metrics, job histories, and logs — yet teams often struggle to transform that raw data into a prioritized, actionable view. The common pain points are familiar: engineers and operators must jump between folders, dig into long job histories, and correlate events to understand why an automation failed. That context-switching slows response, increases cognitive load, and means managers receive either raw dumps they can’t parse quickly or late alerts after a problem has already impacted downstream processes.

Manoj’s brief framed the problem succinctly: surface the folder-level health that matters, summarize recent failures in plain language, and present a curated, evidence-backed report that reduces triage time and keeps stakeholders informed. The goal wasn’t to automate remediation, but to compress detection-to-context into a one-minute read so humans can make fast, confident decisions.

The Implementation

Manoj built a pragmatic, operationally safe prototype that combines targeted polling, evidence collection, LLM summarization, and polished delivery. The design is intentionally read-only and report-focused — it highlights problems and suggests next steps rather than taking automatic corrective actions.

At a technical level, the prototype works like this:

• Folder-level polling. The workflow queries UiPath Orchestrator using its API to gather job metrics across configured folders. It collects counts of running jobs, recent successes, and faulted job counts to establish a folder health snapshot.
• Recent-failure focus. The checker concentrates on a configurable recency window (the submission used a 4-hour window) so the report emphasizes fresh, actionable incidents instead of rehashing stale noise.
• Evidence collection. For folders or jobs with anomalies, the flow pulls related error messages, stack traces and diagnostic snippets. This raw evidence is attached to the report so summaries are traceable back to the source logs.
• LLM-powered summarization. Collected telemetry and logs are fed into a compact LLM pipeline that produces a concise paragraph per folder: what happened, why it likely happened, and recommended next steps. The summary includes a confidence note so engineers know whether to treat the output as a hypothesis or a high-likelihood diagnosis.
• HTML report generation. The system formats results into a visually structured HTML report with folder/job cards, bolded headers, and section backgrounds for quick scanning. Each folder card contains the summary, top error snippets, and links (or attachments) to the original logs.
• Delivery via Outlook. Instead of another dashboard, the prototype emails the HTML briefing to a configured distribution list. That meets teams where they already triage incidents — in their inbox — and makes the report accessible to both engineers and managers.
• Operational logging & configuration. The prototype emits detailed logs for setup and troubleshooting and exposes configuration for the polling cadence, recency window, and folder scope. This makes it straightforward to pilot on a small folder set and tune thresholds before broad rollout.

The submission emphasized reproducibility: clear run instructions, sample API queries, example report templates, and guidance on Orchestrator permissions needed for read-only access.

The Achievements

Even within the short hackathon timeframe, Manoj’s automation delivered tangible, operational wins that make it an attractive candidate for pilot testing:

• Faster awareness and understanding. Folder summaries convert noisy telemetry into a one-minute briefing, drastically reducing time-to-context for on-call engineers. Instead of hunting through logs, teams get the right evidence and next-step suggestions at a glance.
• Actionable reporting for both ops and stakeholders. The HTML brief is presentation-ready and contains both the high-level narrative and technical backing. That makes it suitable for immediate operational triage and for keeping managers informed without overwhelming them with raw logs.
• Reduced context switching. By centralizing folder health and the most relevant logs in one place, engineers avoid hopping across Orchestrator folders and console pages — saving valuable minutes during incident response.
• Safe, non-invasive posture. The read-only design minimizes risk: the system inspects state and suggests actions but never performs remediation. That conservative approach preserves trust while demonstrating clear value.
• Pilot-ready artifacts. Manoj included example reports, API snippets, and run instructions — all the pieces a team needs to run a small proof-of-concept on select folders within days.

Collectively, these outcomes point to measurable operational improvements: lower mean time to acknowledge (MTTA), faster mean time to resolution (MTTR), and better cross-team visibility — outcomes any RPA operations team would welcome.

Why this matters

For organizations running enterprise RPA, undetected or poorly understood Orchestrator failures translate into real business disruption — missed SLAs, manual rework, and unpredictable downstream effects. Manoj’s prototype demonstrates a practical, low-risk way to improve incident awareness: targeted polling, evidence-backed LLM summarization, and polished delivery. It’s a pattern that scales — start with a handful of critical folders, tune thresholds and summaries, then expand — and it preserves human authority while amplifying operator effectiveness. In short: better context, faster decisions, and fewer fire-drills.