AI Lead Qualification & Sales Automation
Built an AI-powered lead qualification and sales automation workflow designed to turn incoming enquiries into organized sales opportunities.
The project demonstrates how AI can be used to process lead information, evaluate enquiries, connect business knowledge to the qualification process, update lead records, send notifications and support consultation scheduling.
Workflow concept:
Lead Capture → AI Qualification → Knowledge-Based Decision → Lead Record → Notification → Consultation Scheduling
The system brings together AI reasoning, business knowledge, data handling and business tools to reduce manual lead processing and help businesses respond to potential customers more efficiently.
Key capabilities:
AI-assisted lead qualification
Business knowledge integration
Automated lead record updates
Email notifications
Consultation scheduling
Workflow automation Potential applications:
Real estate
Solar and home services
Agencies
Consultants
B2B service businesses Project type: AI automation portfolio engineering project.
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AI Knowledge & Support Agent
Built an AI knowledge and support system designed to help users get answers from a controlled business knowledge base rather than relying only on general AI knowledge.
The project explored a Retrieval-Augmented Generation (RAG) workflow where business documents and information can be processed, stored as searchable knowledge, retrieved when relevant, and used to provide more grounded AI responses.
The architecture demonstrates how AI can be connected to an organization's own information to support customer questions, internal knowledge access and repetitive support tasks.
Core workflow:
Knowledge Sources → Processing & Embeddings → Vector Database → Retrieval → AI Response
Key capabilities:
Business knowledge retrieval
RAG-based AI responses
Document/knowledge processing
Vector search with Pinecone
AI-powered question answering
Knowledge-grounded responses Potential applications:
Customer support
Internal company knowledge
SaaS support
E-commerce
Education
Professional services Project type: AI/RAG portfolio engineering project.
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AI Appointment & Business Action Agent
AI Appointment & Business Action Agent
I designed and built a tool-connected AI agent using n8n to demonstrate how an AI assistant can move beyond answering questions and actually interact with business tools.
The workflow receives a request through a Webhook, passes it to an AI Agent, connects the agent to Google Gemini, maintains conversation context with Simple Memory, and gives the agent access to external tools including OpenWeatherMap and Google Calendar.
The agent can use the available tools as part of the workflow and return the result through Respond to Webhook, creating a practical foundation for AI-powered business assistants and automated customer workflows.
Workflow architecture
Webhook → AI Agent → Respond to Webhook
Connected capabilities:
Google Gemini Chat Model
Conversation Memory
OpenWeatherMap
Google Calendar Potential business applications The same architecture can be adapted for businesses that receive repetitive enquiries and need an AI assistant connected to real business actions, including:
Hotels and hospitality
Real estate
Events and entertainment
Field-service businesses
Professional services Technology: n8n, Google Gemini, AI Agent, Webhooks, Google Calendar, OpenWeatherMap and workflow automation. Project type: AI automation / portfolio engineering project.
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Designed and developed a prototype for a Nigerian farm-to-home marketplace connecting customers with fresh agricultural products and suppliers.
The project explored the digital marketplace experience across product discovery, categories, customer interactions and the underlying platform structure required for a scalable marketplace.
Built the prototype with a modern responsive interface and a product-focused architecture designed to support future marketplace, ordering, payment, logistics and administrative functionality.
The prototype was developed as an early-stage product build to validate the concept and user experience before full production deployment.
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