Agentic Workflow for Automated Incident Report Generation and Routing

Manual incident reporting consumes 45-90 minutes of manager time per event, involving interviews, note consolidation, evidence gathering, and form filling. A custom mobile-guided interview agent structures the data capture in real-time, auto-drafting a comprehensive report with attached evidence (photos, CCTV timestamps). This slashes administrative labor by over 70%, freeing management for higher-value guest recovery and operational leadership.

Inconsistent or incomplete reports create legal and insurance vulnerabilities. This workflow enforces a structured interview based on regulatory and corporate policy, ensuring all critical details (witness statements, conditions, immediate actions) are captured. The system timestamps every step, creates an immutable audit trail, and stores all documentation in a secure, centralized case file. This defensible process strengthens your position in claims disputes and regulatory reviews.

Delays in submitting formal reports to insurers or authorities can impact claim settlements and compliance ratings. The workflow includes specialized routing agents that package the finalized report with all evidence and automatically send it to pre-configured internal stakeholders (Risk, Legal) and external contacts (insurance portals, regulatory bodies) based on incident type and severity. This eliminates manual email chains and filing, compressing submission cycles from a week to near-real-time.

Isolated paper or spreadsheet reports offer no operational intelligence. This workflow feeds all structured incident data into a centralized analytics layer. Agents continuously analyze trends—identifying recurring slip-and-fall locations, frequent maintenance-related issues, or time-based security patterns. Management receives automated digests and alerts, enabling data-driven interventions like targeted staff training, preventive maintenance, or security protocol adjustments before minor issues become major liabilities.

For groups or management companies, inconsistent reporting across properties obscures portfolio-wide risk. This custom workflow provides a unified mobile interface and data schema for all locations. Corporate risk and safety teams gain a real-time dashboard of all incidents, with the ability to benchmark properties, identify outliers, and enforce consistent response protocols. This turns a fragmented process into a scalable, centralized control function.

A practical build integrates a mobile front-end (React Native/Flutter) with a backend orchestration engine (LangGraph/CrewAI). Agents handle the interview flow, evidence processing, and routing logic. Integration points include the PMS (for guest/room context), document storage (SharePoint/S3), and email/API channels for external submission. The pilot focuses on a single property, refining the interview script and approval gates (e.g., manager sign-off before insurance submission) before a phased rollout with detailed change management for frontline staff.

This agent orchestrates the initial data capture via a staff member's mobile device. Upon incident logging, it conducts a structured, context-aware interview—asking follow-up questions based on incident type (e.g., slip-and-fall vs. security breach). It validates inputs in real-time (e.g., timestamps, location) and prompts for photo/video evidence, uploading assets directly to a secure evidence locker. This component eliminates incomplete forms and ensures a forensically sound initial record.

This agent ingests the structured interview data, witness statements (from text/voice), and linked evidence metadata. Using a retrieval-augmented generation (RAG) pipeline over policy documents and past incident templates, it drafts a comprehensive narrative report. It highlights inconsistencies for review, auto-populates standardized fields (date, location, involved parties), and formats the draft according to corporate and insurance carrier requirements, ready for human verification.

The core workflow engine that applies business rules to classify incident severity and determine the approval chain. It integrates with the HR system to identify involved employees and their managers, and with directory services to find department heads (Security, Engineering, Risk). It then routes the drafted report, evidence package, and any required action items through a configured sequence—e.g., first to the department head for factual verification, then to the Risk Manager for liability assessment, and finally to insurance contacts via secure API or email.

This is not a single agent but a critical integration subsystem. It provides secure, timestamped storage for all multimedia evidence (photos, videos, CCTV timestamp clips fetched via API from the VMS). It generates hash values for integrity verification and attaches metadata (source, time, location) to each file. This layer ensures evidence is immutably linked to the incident case file and readily available for internal review or insurance submission, replacing manual, error-prone file gathering.

A centralized web dashboard where managers and risk personnel review drafted reports, annotated evidence, and agent-highlighted discrepancies. Reviewers can request clarifications, add notes, or reject the draft back to the synthesis agent with comments. Approved reports trigger automatic notifications to the next person in the chain and final archival in the document management system (e.g., SharePoint, ServiceNow). This component provides necessary governance, ensuring human oversight is focused on high-value judgment, not administrative assembly.

An observability agent that monitors the status of all submitted reports. It tracks acknowledgments from external insurance portals, flags any follow-up requests, and schedules reminders for internal follow-up actions (e.g., corrective measures). It also maintains a complete, immutable log of all workflow steps, user interactions, and data changes for compliance audits. This transforms incident reporting from a point-in-time task into a managed, closed-loop process with full accountability.

This stakeholder defines the report structure, evidence requirements, and legal defensibility standards. They own the liability exposure and insurance relationships. The workflow must produce court-ready documentation with a clear audit trail of actions, timestamps, and approvals. Their sign-off is critical for governance and determines the escalation logic to insurance contacts.

Hotel staff (security, front desk, housekeeping) are the primary users who log incidents via the mobile interface. The workflow's success hinges on intuitive, guided data capture that minimizes disruption to their duties. The agentic interview must be fast, context-aware, and supportive—replacing stressful form-filling with a structured conversational agent that ensures all necessary details (witnesses, photos, location) are collected at the scene.

This team architects the connections between the mobile app, PMS (e.g., Opera), security camera systems, document storage, and internal communication platforms (e.g., Microsoft Teams, Slack). They ensure the workflow agents can retrieve video timestamps, attach media, and push finalized reports to the correct departmental heads via existing channels. They also implement the observability layer for monitoring workflow health and exception rates.

Heads of Security, Engineering, and Guest Services are the primary internal recipients of routed reports. They require reports that are immediately actionable, with clear summaries, attached evidence, and recommended next steps. The workflow must include configurable approval gates for them to acknowledge, escalate, or request amendments before reports are finalized or sent externally. Their feedback loop is essential for refining report accuracy and relevance.

This stakeholder validates the data retention policy, audit trail design, and privacy controls (e.g., blurring faces in public area photos). They ensure the automated drafting agent adheres to jurisdictional reporting requirements and that the system's outputs can withstand regulatory or legal scrutiny. Their review is mandatory for the final report template and any AI-generated narrative to mitigate hallucination risk.

Often a cross-functional team or external partner, this role manages the pilot deployment, staff training, and iterative refinement based on real-world use. They design the rollout sequence (e.g., pilot property, then region-wide), create training materials for the mobile app, and establish feedback channels to capture edge cases (e.g., complex multi-party incidents) that require human-in-the-loop routing.