Field Services

Cookbooks are a series of examples illustrating real-world use cases where Contextual speeds development and improves outcomes.

Business Goal / Challenge:

A field services organization wanted a way to streamline work order completion using AI to better categorize and prioritize client requests. Their clients use a range of different workflow management systems and each client has their own methods of categorizing work, defining tasks, designating priority, and supplying commentary. As a result, work requests had inconsistent data that made streamlining operations difficult and required significant manual intervention.

AI Solution Approach:

Interpreting human-generated work orders and categorizing data from disparate systems is an ideal challenge for generative AI. With the right prompt structure and output formats, generative AI can consistently organize, summarize and make the content actionable. The resulting requests can then be managed through a single operations system with dependable automation.

Contextual Orchestration:

Ingest Enterprise Feeds - Contextual polls and subscribes to multiple client work order request systems (i.e. Corrigo, ServiceChannel, Vue, ServiceNow) to retrieve work orders in any format.
Extract Fixed Data - Well-defined and easily mapped fields such as Created Date or Due by Date are extracted from the customer-specific systems into an ITSM consistent service request format.
Enrich with Third-Party Sources - Third-party data like local weather events or emergency conditions is retrieved to further optimize prioritization and scheduling.
Execute AI Assistants - Custom AI Agents trained to standardize priorities, tasks and actions produce a consistent and complete service request regardless of client system differences, manual instructions or human variability.
Deliver AI-enriched Results - The service request is delivered into the customer’s operations system (Salesforce) as a Salesforce Case to drive efficient processes.
Tune and Improve - Expert user feedback is fed back into the AI Agent to tune performance and maintain accuracy regardless of changing business conditions.

By integrating Contextual within the enterprise, your organization can not only streamline operations but also unlock new levels of intelligence, efficiency, and value from your existing infrastructure. Our AI-powered platform is designed to adapt to your specific needs, providing a robust, scalable solution that evolves with your business.

PreviousIndustry Cookbooks NextTenant Workspace

Last updated 10 months ago

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Business Goal / Challenge:

AI Solution Approach:

Contextual Orchestration:

Ingest Enterprise Feeds - Contextual polls and subscribes to multiple client work order request systems (i.e. Corrigo, ServiceChannel, Vue, ServiceNow) to retrieve work orders in any format.

Extract Fixed Data - Well-defined and easily mapped fields such as Created Date or Due by Date are extracted from the customer-specific systems into an ITSM consistent service request format.

Enrich with Third-Party Sources - Third-party data like local weather events or emergency conditions is retrieved to further optimize prioritization and scheduling.

Execute AI Assistants - Custom AI Agents trained to standardize priorities, tasks and actions produce a consistent and complete service request regardless of client system differences, manual instructions or human variability.

Deliver AI-enriched Results - The service request is delivered into the customer’s operations system (Salesforce) as a Salesforce Case to drive efficient processes.

Tune and Improve - Expert user feedback is fed back into the AI Agent to tune performance and maintain accuracy regardless of changing business conditions.