AI Agents (Assistants) on Company Knowledge, No Code Training Course
An intelligent assistant leveraging institutional records can provide authoritative responses regarding policies, operational manuals, and procedural workflows, while explicitly citing the source material. This course demonstrates the methodology for preparing documents for AI ingestion, selecting appropriate platforms, deploying agents without programming, and evaluating response accuracy using standardized question sets. Participants will also develop a comprehensive maintenance strategy.
This instructor-led, live training, available online or on-site, is designed for teams, subject matter experts, and key users tasked with delivering accurate information from organizational documents, policies, and manuals.
Upon completion of this training, participants will be able to:
- Comprehend the underlying principles of AI document retrieval (Retrieval-Augmented Generation) and recognize its operational boundaries
- Prepare and structure documents to ensure the accuracy of generated responses
- Identify and select the most suitable platform for implementing a knowledge agent for government
- Configure and deploy a shared knowledge agent without requiring coding expertise
- Validate system outputs using a structured question catalog and verify source citations
- Establish protocols for maintenance, role assignment, and content currency in an operational environment
Course Structure
- Duration: One day (seven hours)
- Interactive instruction led by an expert trainer, incorporating discussion and hands-on exercises focused on participants' specific use cases
- Outcome: Each participant will have a functional shared knowledge agent, a measured accuracy rate, and a documented maintenance plan.
Customization Options
- To arrange a tailored training session specific to this curriculum, please contact the provider directly.
Course Outline
- Day 1: Transitioning from static document repositories to intelligent knowledge systems for government
- Mechanisms by which AI systems retrieve and synthesize information from institutional records
- Locating information within archives and providing citation-ready responses
- Common causes for inaccurate, incomplete, or erroneous outputs
- Distinguishing between standalone file uploads and integrated digital repository structures
- Practical application: Identify three representative inquiries requiring authoritative responses for government operations.
- Optimizing knowledge assets
- Ensuring logical structure, consistent nomenclature, and content currency
- Eliminating redundancy and resolving conflicting versions of policy or procedure
- Verifying access permissions and classification levels
- Practical application: Audit the existing document set and curate a refined, verified selection for the system.
- Selecting a deployment platform
- Implementing a Copilot agent within SharePoint environments
- Utilizing Claude projects or custom GPT configurations
- Employing Langdock assistants or NotebookLM tools
- Evaluation criteria including data residency, sharing protocols, repository capacity, and fiscal impact
- Practical application: Select the optimal platform for the specific operational context and document the justification.
- Configuring the agent
- Defining operational parameters including target audience, communication tone, and output formatting
- Mandating explicit source attribution in all generated responses
- Protocols for handling queries that exceed the scope of the available knowledge base
- Practical application: Deploy the knowledge agent on the selected platform using established configurations.
- Validating performance via a question catalog
- Developing a set of 20 validation queries with predetermined expected outcomes
- Categorizing responses as accurate, partially accurate, incorrect, or lacking
- Refining system instructions and underlying documents based on performance data
- Practical application: Execute the validation test with 20 queries and document the accuracy rate.
- Ongoing maintenance and administration
- Establishing clear accountability for content integrity
- Managing updates, version control, and lifecycle status
- Systematically gathering and analyzing user feedback
- Practical application: Draft a maintenance protocol specifying roles, responsibilities, and review cadences.
- Deliverables: Each participant will possess a operational knowledge agent for government use, a documented accuracy metric, and a formal maintenance plan.
- Mechanisms by which AI systems retrieve and synthesize information from institutional records
Requirements
- Access to Copilot, Claude, ChatGPT, Langdock, or NotebookLM, along with a collection of approved, final-release documents relevant to the participant’s domain.
- Programming proficiency is not a requirement.
Target Audience
- Teams, subject matter experts, and key users responsible for providing accurate information derived from organizational documents, policies, and manuals.
Runs with a minimum of 4 + people. For 1-to-1 or private group training, request a quote.
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