AI-Powered Event Input Brief Generator
Revolutionizing Strategic Event Planning for George P. Johnson (GPJ)
Client: George P. Johnson (GPJ), a global leader in event management.
Role: Technical Manager
Tech Stack: React, FastAPI, RabbitMQ, MongoDB, Azure, FAISS, OpenAI Embedding, IBM WatsonX
Generative AI
RAG
Overview
Streamline the creation of event input briefs—critical documents for event kickoffs—using AI to reduce manual effort by 70% and cut generation time from 3 weeks to 5 days.
Using contextual documents, it uses AI to find the appropriate information for a document with multiple fields.
Key Features
AI-Driven Workflow Automation
Section-by-Section Wizard: Guided users through six critical brief sections (Project Overview, Stakeholders, Objectives, etc.), combining AI generated responses and manual inputs.
Multi-Source Data Integration: Auto-populated fields using Google Sheets, uploaded documents (PDF, DOC, CSV), and AI-extracted insights from unstructured data.
IBM WatsonX & RAG Pipeline: Utilized Retrieval-Augmented Generation (RAG) to analyze documents, generate structured responses, and ensure context-aware content aligned with GPJ’s strategic goals.
Role-Based Collaboration
User Roles: Admins, GPJ Account Managers, Strategists, and Clients (e.g., IBM) with tailored permissions (edit, approve, read-only).
Approval Workflows: Integrated email notifications to ensure stakeholders reviewed and approved sections before finalising briefs.
Tech Stack:
Frontend: React.js
Python(FastAPI)
RabbitMQ
MongoDB
Azure Blob Storage
Azure Container Instances
IBM WatsonX
FAISS vectorDB, RAG
OpenAI embedding model
My Contribution
Led the project as the Lead Technical Manager from discovery to delivery, managing stakeholder expectations, project timelines, budgets, and overall execution strategy.
Product Requirements & Documentation: Created the Product Requirements Specification (PRS) and supporting technical documents, ensuring alignment between business needs, user workflows, and technical feasibility.
Stakeholder Collaboration: Acted as the bridge between GPJ stakeholders, internal development teams, and cloud/AI vendors, facilitating agile sprint reviews, UATs, and approvals across cross-functional groups.
Solution Design and Development Leadership: Architected the technical solution (React.js + FastAPI + Azure + AI/RAG pipeline) and led the engineering team to implement a secure, scalable, and AI-enhanced platform.
AI Integration: Architected the Retrieval-Augmented Generation (RAG) pipeline using IBM WatsonX, FAISS vector database, and OpenAI embedding models to intelligently process user-uploaded documents and structured data inputs.
Project Execution and Risk Management: Monitored progress, proactively identified risks, and course-corrected to ensure on-time delivery, achieving a 70% reduction in input brief creation time
Impact & Recognition
Achieved rapid user adoption across multiple GPJ departments, exceeding initial KPI goals for project turnaround time and approval workflow efficiency.
Time Reduction: Successfully reduced the event input brief creation cycle from 3 weeks to just 5-7 days, achieving a ~70% reduction in manual effort.
Increased Strategic Alignment: Enhanced collaboration between GPJ teams and clients (e.g., IBM) through a centralized, transparent, and role-driven platform.
Efficiency Boost: Automated data extraction and AI-assisted writing improved brief accuracy, minimized rework, and increased stakeholder confidence in the system.
First-of-its-Kind Deployment: Positioned GPJ as a leader in AI-driven event planning within the event management industry.
Takeaway
AI Should Empower, Not Replace: Building AI tools that assist and empower users—rather than trying to fully automate complex human tasks—creates much higher adoption and trust.
Regular demos, feedback sessions, and active involvement of business stakeholders during sprints were critical to aligning the product to real-world needs.
Retrieval-Augmented Generation pipelines need careful document preparation and tuning to ensure relevance and accuracy—especially when different data formats are involved.
The scrum-based approach with clear milestone planning helped manage scope, prioritize critical features, and deliver a production-ready tool within tight timelines.
More Works
FAQ
01
What kinds of projects have you managed?
02
What industries have you worked in?
03
What technical skills do you bring to the table?
04
What project management methodologies are you most familiar with?
05
Do you have experience managing remote or distributed teams?
06
How do you handle project risks and escalations?
07
What is your leadership style?
08
Are you open to freelance consulting / side projects ?
AI-Powered Event Input Brief Generator
Revolutionizing Strategic Event Planning for George P. Johnson (GPJ)
Client: George P. Johnson (GPJ), a global leader in event management.
Role: Technical Manager
Tech Stack: React, FastAPI, RabbitMQ, MongoDB, Azure, FAISS, OpenAI Embedding, IBM WatsonX
Generative AI
RAG
Overview
Streamline the creation of event input briefs—critical documents for event kickoffs—using AI to reduce manual effort by 70% and cut generation time from 3 weeks to 5 days.
Using contextual documents, it uses AI to find the appropriate information for a document with multiple fields.
Key Features
AI-Driven Workflow Automation
Section-by-Section Wizard: Guided users through six critical brief sections (Project Overview, Stakeholders, Objectives, etc.), combining AI generated responses and manual inputs.
Multi-Source Data Integration: Auto-populated fields using Google Sheets, uploaded documents (PDF, DOC, CSV), and AI-extracted insights from unstructured data.
IBM WatsonX & RAG Pipeline: Utilized Retrieval-Augmented Generation (RAG) to analyze documents, generate structured responses, and ensure context-aware content aligned with GPJ’s strategic goals.
Role-Based Collaboration
User Roles: Admins, GPJ Account Managers, Strategists, and Clients (e.g., IBM) with tailored permissions (edit, approve, read-only).
Approval Workflows: Integrated email notifications to ensure stakeholders reviewed and approved sections before finalising briefs.
Tech Stack:
Frontend: React.js
Python(FastAPI)
RabbitMQ
MongoDB
Azure Blob Storage
Azure Container Instances
IBM WatsonX
FAISS vectorDB, RAG
OpenAI embedding model
My Contribution
Led the project as the Lead Technical Manager from discovery to delivery, managing stakeholder expectations, project timelines, budgets, and overall execution strategy.
Product Requirements & Documentation: Created the Product Requirements Specification (PRS) and supporting technical documents, ensuring alignment between business needs, user workflows, and technical feasibility.
Stakeholder Collaboration: Acted as the bridge between GPJ stakeholders, internal development teams, and cloud/AI vendors, facilitating agile sprint reviews, UATs, and approvals across cross-functional groups.
Solution Design and Development Leadership: Architected the technical solution (React.js + FastAPI + Azure + AI/RAG pipeline) and led the engineering team to implement a secure, scalable, and AI-enhanced platform.
AI Integration: Architected the Retrieval-Augmented Generation (RAG) pipeline using IBM WatsonX, FAISS vector database, and OpenAI embedding models to intelligently process user-uploaded documents and structured data inputs.
Project Execution and Risk Management: Monitored progress, proactively identified risks, and course-corrected to ensure on-time delivery, achieving a 70% reduction in input brief creation time
Impact & Recognition
Achieved rapid user adoption across multiple GPJ departments, exceeding initial KPI goals for project turnaround time and approval workflow efficiency.
Time Reduction: Successfully reduced the event input brief creation cycle from 3 weeks to just 5-7 days, achieving a ~70% reduction in manual effort.
Increased Strategic Alignment: Enhanced collaboration between GPJ teams and clients (e.g., IBM) through a centralized, transparent, and role-driven platform.
Efficiency Boost: Automated data extraction and AI-assisted writing improved brief accuracy, minimized rework, and increased stakeholder confidence in the system.
First-of-its-Kind Deployment: Positioned GPJ as a leader in AI-driven event planning within the event management industry.
Takeaway
AI Should Empower, Not Replace: Building AI tools that assist and empower users—rather than trying to fully automate complex human tasks—creates much higher adoption and trust.
Regular demos, feedback sessions, and active involvement of business stakeholders during sprints were critical to aligning the product to real-world needs.
Retrieval-Augmented Generation pipelines need careful document preparation and tuning to ensure relevance and accuracy—especially when different data formats are involved.
The scrum-based approach with clear milestone planning helped manage scope, prioritize critical features, and deliver a production-ready tool within tight timelines.
More Works
FAQ
01
What kinds of projects have you managed?
02
What industries have you worked in?
03
What technical skills do you bring to the table?
04
What project management methodologies are you most familiar with?
05
Do you have experience managing remote or distributed teams?
06
How do you handle project risks and escalations?
07
What is your leadership style?
08
Are you open to freelance consulting / side projects ?
AI-Powered Event Input Brief Generator
Revolutionizing Strategic Event Planning for George P. Johnson (GPJ)
Client: George P. Johnson (GPJ), a global leader in event management.
Role: Technical Manager
Tech Stack: React, FastAPI, RabbitMQ, MongoDB, Azure, FAISS, OpenAI Embedding, IBM WatsonX
Generative AI
RAG
Overview
Streamline the creation of event input briefs—critical documents for event kickoffs—using AI to reduce manual effort by 70% and cut generation time from 3 weeks to 5 days.
Using contextual documents, it uses AI to find the appropriate information for a document with multiple fields.
Key Features
AI-Driven Workflow Automation
Section-by-Section Wizard: Guided users through six critical brief sections (Project Overview, Stakeholders, Objectives, etc.), combining AI generated responses and manual inputs.
Multi-Source Data Integration: Auto-populated fields using Google Sheets, uploaded documents (PDF, DOC, CSV), and AI-extracted insights from unstructured data.
IBM WatsonX & RAG Pipeline: Utilized Retrieval-Augmented Generation (RAG) to analyze documents, generate structured responses, and ensure context-aware content aligned with GPJ’s strategic goals.
Role-Based Collaboration
User Roles: Admins, GPJ Account Managers, Strategists, and Clients (e.g., IBM) with tailored permissions (edit, approve, read-only).
Approval Workflows: Integrated email notifications to ensure stakeholders reviewed and approved sections before finalising briefs.
Tech Stack:
Frontend: React.js
Python(FastAPI)
RabbitMQ
MongoDB
Azure Blob Storage
Azure Container Instances
IBM WatsonX
FAISS vectorDB, RAG
OpenAI embedding model
My Contribution
Led the project as the Lead Technical Manager from discovery to delivery, managing stakeholder expectations, project timelines, budgets, and overall execution strategy.
Product Requirements & Documentation: Created the Product Requirements Specification (PRS) and supporting technical documents, ensuring alignment between business needs, user workflows, and technical feasibility.
Stakeholder Collaboration: Acted as the bridge between GPJ stakeholders, internal development teams, and cloud/AI vendors, facilitating agile sprint reviews, UATs, and approvals across cross-functional groups.
Solution Design and Development Leadership: Architected the technical solution (React.js + FastAPI + Azure + AI/RAG pipeline) and led the engineering team to implement a secure, scalable, and AI-enhanced platform.
AI Integration: Architected the Retrieval-Augmented Generation (RAG) pipeline using IBM WatsonX, FAISS vector database, and OpenAI embedding models to intelligently process user-uploaded documents and structured data inputs.
Project Execution and Risk Management: Monitored progress, proactively identified risks, and course-corrected to ensure on-time delivery, achieving a 70% reduction in input brief creation time
Impact & Recognition
Achieved rapid user adoption across multiple GPJ departments, exceeding initial KPI goals for project turnaround time and approval workflow efficiency.
Time Reduction: Successfully reduced the event input brief creation cycle from 3 weeks to just 5-7 days, achieving a ~70% reduction in manual effort.
Increased Strategic Alignment: Enhanced collaboration between GPJ teams and clients (e.g., IBM) through a centralized, transparent, and role-driven platform.
Efficiency Boost: Automated data extraction and AI-assisted writing improved brief accuracy, minimized rework, and increased stakeholder confidence in the system.
First-of-its-Kind Deployment: Positioned GPJ as a leader in AI-driven event planning within the event management industry.
Takeaway
AI Should Empower, Not Replace: Building AI tools that assist and empower users—rather than trying to fully automate complex human tasks—creates much higher adoption and trust.
Regular demos, feedback sessions, and active involvement of business stakeholders during sprints were critical to aligning the product to real-world needs.
Retrieval-Augmented Generation pipelines need careful document preparation and tuning to ensure relevance and accuracy—especially when different data formats are involved.
The scrum-based approach with clear milestone planning helped manage scope, prioritize critical features, and deliver a production-ready tool within tight timelines.
More Works
FAQ
What kinds of projects have you managed?
What industries have you worked in?
What technical skills do you bring to the table?
What project management methodologies are you most familiar with?
Do you have experience managing remote or distributed teams?
How do you handle project risks and escalations?
What is your leadership style?
Are you open to freelance consulting / side projects ?