Agent Factory Enablement

Service Overview

The EDB Agent Factory Enablement engagement moves beyond infrastructure to deliver working AI use cases. An EDB Solution Architect and Senior Consultant work directly with your teams for up to 120 hours to design, build, and deploy production-ready AI applications using EDB Agent Factory — including RAG applications, AIOps runbooks, and agentic workflows.

This engagement is use-case-led: EDB starts by understanding your specific business problem and data landscape, then guides your team through every step from knowledge base construction to live workflow deployment. Your team participates throughout, building the hands-on skills to maintain and extend the solution independently.

Note: Agent Factory Enablement assumes EDB Agent Factory is already deployed. If not, see the Agent Factory Deployment engagement.

Scope of Service

Onboard

• Kickoff to align stakeholders, confirm environment readiness, and define use case scope  to fit estimated effort. 
• Review existing data landscape: sources, formats, volumes, governance requirements
• Identify target personas and success criteria

Discovery & Use Case Design

• Conduct structured use case discovery sessions with business and technical stakeholders
• Define knowledge base structure: data sources, chunking strategy, metadata schema for hybrid search
• Design agentic workflow topology: agent roles, tool inventory, escalation logic, human-in-the-loop checkpoints
• Document AIOps runbook logic for automated incident response scenarios

Implementation

• Build and configure knowledge base ingestion pipelines from agreed data sources
• Implement hybrid search (vector + BM25) for each knowledge base
• Construct and test agentic workflows in LangFlow for each agreed use case
• Configure model routing and prompt engineering for each workflow
• Develop and register custom MCP tools in the Tool Repository
• Build and test AIOps runbook with automated execution and audit logging

Deployment & Validation

• Deploy implemented use cases to the target environment
• Conduct end-to-end scenario testing with customer team participation
• Validate accuracy, latency, and audit trail for each deployed use case
• Demonstrate key scenarios: query the knowledge base, trigger an agent workflow, review audit output

Knowledge Transfer & Closure

• Conduct hands-on knowledge transfer sessions with customer team
• Walk through workflow configuration, knowledge base management, and model tuning
• Deliver implementation documentation and operational runbook

• Provide recommended next steps for extending the Agent Factory use case portfolio

   

Deliverables

• Deployed and operational AI use case per agreed scope
• Configured knowledge base pipelines with documented ingestion configuration
• Documented agentic workflows (exported LangFlow configurations)
• Registered custom MCP tools with API documentation
• Engagement summary with implementation notes and extension recommendations

Roles and Responsibilities

EDB Project Manager: responsible for engagement planning, stakeholder coordination, schedule management, and closeout.

EDB Solution Architect: leads use case design, knowledge base architecture, and agentic workflow design. Ensures solution aligns with EDB Agent Factory capabilities and customer data governance requirements.

EDB Senior Consultant: technical lead for all implementation, testing, deployment, and knowledge transfer activities.

Customer Team: active participants throughout the engagement. Key roles:

• Data Owner / Data Engineer (required for knowledge base sessions)
• Software Engineer or AI Developer (required for workflow implementation sessions)
• SRE / Operations Lead (required for AIOps use cases)
• Business Stakeholder (required for use case discovery)

Assumptions

• EDB Agent Factory infrastructure is deployed and operational prior to this engagement (see Agent Factory Deployment).
• A kickoff call will confirm scope and schedule before work begins.
• Engagement is delivered remotely unless otherwise agreed.
• Customer will make subject matter experts available for use case discovery sessions.
• Customer data used for knowledge base construction is non-sensitive or has been appropriately anonymized.
• Use cases are scoped to non-production environments unless otherwise agreed.
• LLM model selection and configuration is finalized prior to implementation.
• Customer will provide timely feedback on deliverables. Items without commentary within 5 business days are deemed accepted.
• Customer will not provide Personal Data as defined by applicable law.
• Application integration with external production systems (beyond MCP tool stubs) is out of scope.
• EDB will provide up to 120 hours, plus project management, to support the above activities. Additional efforts will require mutually agreed upon change control. 

Prerequisites

• EDB Agent Factory environment is deployed and validated (Agent Factory Deployment engagement or equivalent).
• Customer has identified use case and has executive sponsorship for the engagement.
• Source data for knowledge base is accessible and customer has necessary read permissions.
• For AIOps use cases: customer has access to target systems (ticketing, monitoring, network APIs) and appropriate credentials.
• Customer team members who will participate have calendar availability confirmed for engagement duration.
• EDB Hybrid Manager and Agent Factory components are running and accessible to EDB consultants.

Engagement Activities