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Hi, I’m Chamith
Practical AI Consulting Automation & Workflow Building Lead Generation Strategy

I help businesses through practical, results-driven digital systems— from lead generation to automation to data-backed campaigns. Over the past few years, I've worked with local and online clients— including gyms, flight schools, and home service providers — to generate qualified leads, save time through automation, and increase revenue with smarter, more efficient systems. My focus is always the same: real outcomes, measurable ROI, and solutions that make a tangible difference to the bottom line.

Services

What I Do

Operational AI Consulting

Automate lead generation, appointment booking, and client engagement—using AI chatbots, CRM flows, and smart workflows to save time and convert more leads.

Data-Driven Business Insights

Use AI-powered analytics to track, measure, and optimize campaigns. Real-time dashboards show leads, conversion rates, and pipeline value across all platforms—clearly and instantly. Smarter insights. Faster decisions. Better ROI.

Social Media Strategy

Designing high-performance campaigns with AI-powered targeting, audience segmentation, and content automation to boost reach and conversions.

View my portfolio

My Portfolio

Consulting Projects

Consulting Projects | Personal

RP Plumbing & Gardening

Client: A local landscaping and plumbing business based in Swansea, Wales. They wanted to move beyond word-of-mouth and build a steady flow of new clients online.

Objective: Help move their business online and create a repeatable, automated lead generation system that could help them stand out in a crowded local market and support long-term growth.

Deliverables:

Website & Chatbot setup: Built a clean, high-converting website with an integrated lead form and chatbot to answer questions, handle inquiries, bookings, and basic questions.
Smart Business Cards: Designed scannable business cards linking directly to the booking page— making it easy for existing customers to refer friends and for offline leads to convert online.
Social Presence: Set up and managed their social pages, using automated content scheduling so they stayed active without extra effort from the client.
Lead Follow Up: Connected everything to a CRM that sent automated follow-ups via SMS and email. The owner received a text every time a form was filled out — no more chasing cold leads manually.

Impact: Within six weeks, they saw a 40% increase in inquiries, most of it coming from Facebook traffic. Robert (the owner) was able to spend more time on actual jobs while the system brought in consistent leads in the background.

Consulting Projects

Popadoms Resturant

Client: Popadoms — a well-known family-run Asian restaurant in Newport, looking to boost online orders and reach more local customers through social media.

Objective: Run a short, high-impact campaign to increase online orders and improve customer engagement, especially during weekday evenings when traffic was slower.

Deliverables:

Ad Campaign Strategy: Designed and launched a 14-day Meta (Instagram + Facebook) campaign featuring their most popular dishes and promotions, targeted to local foodies and repeat customers.
Budget & Performance Management: Ran the campaign with a £350 budget, keeping CPC under £1.50 and achieving a strong 3% conversion rate.
Performance Metrics:
- Return on Ad Spend (ROAS): Achieved a 300% ROAS
- Cost Per Click (CPC): Maintained a CPC of £1.50
- Conversion Rate: 3%

Impact: The campaign brought in over 150 inquiries, resulting in a ~15% increase in online orders that month. Repeat customers responded well to personalized offers, and the data helped the client see exactly which promotions were working.

Consulting Projects

TNT Fitness

Client: Tiyapo Adeoye — retired professional bodybuilder and gym owner based in Watford, looking to boost sign-ups and streamline communication with new leads.

Objective: Increase gym membership sign-ups through a stronger digital presence, automation, and a high-engagement social media campaign.

Key Strategies and Metrics:

Website Development: Built a clean, mobile-friendly website with an integrated class schedule and lead form. Set up WhatsApp notifications so Tiyapo was instantly alerted whenever someone booked a session.
Meta Giveaway Campaign: Launched an engaging social media giveaway offering a free training session to attract potential gym members nearby.
Campaign Achievements:
- Engagement and Reach: Over 1,000 people interacted with the campaign
- High Conversion Rate: 14 new paying members signed up in the first month
- Cost-Effective Acquisition: Just £4.50 per new member

Impact: The campaign turned digital engagement into real revenue. Automated follow-ups helped reduce drop-offs and improved retention. With systems in place, Tiyapo was able to focus more on coaching while the backend handled lead capture, follow-up, and scheduling.

Consulting Projects

Aerolift Aviation Academy

Client: Aerolift Flight Academy — a family-owned flight school based in Michigan.

Objective: Increase student enrollment and revenue by building a simple but effective marketing funnel to promote their introductory flight lessons.

Strategy and Execution:

Marketing Funnel Development: Worked closely with the academy’s owner to build a streamlined marketing funnel that guided potential students from awareness to enrollment.
Meta Lead Generation Campaign: Launched a targeted lead generation campaign on Meta (Facebook/Instagram) aimed at aspiring pilots in the surrounding area.
Automation & Consistency: Set up an automated system using Zapier and ClickFunnels to capture, qualify, and follow up leads— removing the need for constant manual outreach.
New Enrollments: 2 new Private Pilot License (PPL) students signed up in the first two weeks.
Revenue Growth: Generated $10, 000 in additional revenue within the first month.
Ongoing Success: The funnel continues to bring in steady leads each month, providing a predictable and scalable acquisition channel.

Impact: This project reinforced how powerful a well-built funnel and focused targeting can be—especially for niche service businesses. It also reinforced the value of clarity, simplicity, and automation when building digital systems that convert.

Consulting Projects

SJ Fitness

Client: SJ Fitness — run by Samantha Connell, a professional bodybuilder and gym owner based in Blackpool, Wales.

Objective: Increase bookings for SJ Fitness’s weight loss programs by improving digital visibility and building a consistent, low-maintenance lead generation system.

Key Strategies and Metrics:

Website Funnel Development: Built a clear, mobile-friendly website funnel that simplified the booking process and captured leads more effectively.
Social Media Content Creation: Created and scheduled engaging social media posts across Instagram and Facebook, focusing on client results and program benefits.
Localised Meta Ads: Launched a targeted Meta campaign aimed at people in the local area actively looking for weight loss support.

Campaign Achievements:

Boosted Online Presence: The new website and content strategy .brought in significantly more engagement and visibility.
Lead Growth: The Meta campaign brought in a consistent stream of qualified leads.
Higher Conversions: A strong percentage of those leads converted into paying clients, raising overall program enrollment rates.

Impact: The combination of a clean funnel, social proof-driven content, and precise ad targeting helped SJ Fitness increase program bookings and grow their client base— all while freeing Samantha up to focus more on coaching and less on day-to-day marketing tasks.

Consulting Projects

Marketing Campaign Highlights (Selected Projects)

🟧 Sweet Greeks Winter Campaign

Client: The Sweet Greeks — a cozy Mediterranean café looking to increase traffic and online orders during quieter winter months.

Objective: Drive engagement, increase visibility, and convert video viewers into online orders using Meta ads.

Deliverables:

Ad Creative A/B Testing: Used two ad variants and kept both running due to equal performance.
Meta Video Campaign: Targeted local food lovers on Facebook and Instagram with snackable video content.
Tracking Setup: Measured impressions, unique clicks, engagements, and hook rate to refine performance.

Impact:

Reach: 27,556
Post Engagement: 11,113
Unique Clicks: 501
Hook Rate: 24.25%
CTR: 1.1%
CPM: £2.74 — cost-effective and below average

🟩 JamaicaWahGwaan ‘January Discount’ Campaign

Client: Jamaican fast food brand offering a limited-time January discount to boost early-year sales.

Objective: Generate leads and online orders through attention-grabbing Meta video ads.

Deliverables:

Video Ad Design: Produced a short-form ad highlighting the brand’s story, team, and bold Jamaican flavours — layered with messaging around the January discount to drive urgency.
Meta Distribution: Ran the ad across Facebook and Instagram targeting local takeaway customers using geofencing and interest filters.
Performance Tracking: Monitored reach, impressions, clicks, CPC, and CTR to evaluate campaign effectiveness and optimize mid-flight.

Impact:

Reach: 2,232
Impressions: 4,699
Link Clicks: 54
Post Engagement: 517
CPC: £0.28
CTR: 1.13%

🟦 33% Discount Campaign (Unique Health & Fitness)

Client: Unique Health & Fitness: A local gym aiming to drive January sign-ups by offering a limited-time 33% discount for couples.

Objective: Quickly generate leads and increase gym visits through a high-impact Meta ad campaign targeting health-conscious partners.

Deliverables:

Ad Visual: Designed bold, eye-catching visuals focused on transformation, community, and the limited-time couple’s offer.
Meta Targeting: Used Meta’s demographic tools to target couples aged 25–45 within a 10-mile radius who had recently shown fitness interest.
Performance Tracking: Measured CPC and ROI with a lean budget

Impact:

Reach: 16,157
Link Clicks: 142
CPC/CPM: £2.48 per 1,000 people
Outcome:
High ROI, direct gym conversions, and strong cost-efficiency – proving even small campaigns can deliver measurable real-world results.

🟪 Kefy Site Revamp

Client: Kefy – an activewear brand looking to level up their online store by improving user experience, conversion performance, and search visibility.

Objective: Boost on-site engagement, streamline navigation, and improve conversions through UX, SEO, and CRO-focused improvements

Deliverables:

UX Overhaul: Redesigned the site with faster load times, mobile-first layouts, simplified navigation, and a cleaner visual hierarchy to improve usability and reduce drop-off.
Conversion Optimisation: Rebuilt the product structure and checkout process to reduce friction, added real-time live support, and tested CTA placements for better flow.
SEO Enhancements: Conducted deep keyword research and rewrote key pages with high-performing descriptions, conversion-driven content, and technical SEO best practices.

Programming Projects

Solarwise Hybrid Solar Forecasting Model

Objective: Improve the accuracy of short-term solar energy (PV) forecasts by predicting how different cloud conditions affect output — helping solar operators better manage grid integration..

Methodology:

Hybrid CNN/ResNet Model: Trained a hybrid neural network that combined image analysis (CNN) with time-sensitive data modeling (ResNet) to predict solar output based on sky condition images.
Condition-Specific Forecasting: Built separate sub-models to handle four distinct weather types — clear, partly cloudy, mostly cloudy, and overcast. varying sky conditions.
Data & Training: Used 600 labeled sky images from Stanford’s dataset. The model was trained to make 10-minute-ahead PV output forecasts.

Key Outcomes:

Achieved Root Mean Squared Error (RMSE) values as follows: Clear (1.91), Partly-cloudy (1.72), Mostly-cloudy (1.13), and Overcast (4.48). The model excelled with mostly-cloudy conditions but faced challenges with overcast scenarios, likely due to the unpredictability of dense cloud cover.
Contribution & Future Scope: This hybrid approach could help solar operators better plan energy usage under changing weather conditions. With added meteorological inputs (like wind speed or humidity), the model could evolve into a real-time forecasting tool with broader applications in smart grid systems.

Explore More: For a detailed overview of the project’s development and methodology, visit the GitHub repository: Solarwise Project on GitHub

Programming Projects

Land Cover Insights: SVM vs. CNN

Objective: To Build a machine learning system to classify land cover types (like urban, forest, farmland, etc.) from satellite imagery using a combination of supervised and unsupervised learning models..

Key Components:

Dataset: Used the UC Merced Land Use Dataset — 2,100 images across 21 land use categories. These included both high- and low-resolution RGB images.
Methodology:
- Data Handling: Split images into 80% training, 10% validation, and 10% testing sets..
- Feature Extraction : Focused on Histogram of Oriented Gradients (HOG) to capture shape and texture data.
- Algorithms Used: Applied a range of models — K-Means, Gaussian Mixture Models, Support Vector Machines (SVM), and Neural Networks.
- Model Evaluation: Used confusion matrices and accuracy metrics to assess each model’s performance.

Key Outcomes:

Strong Classification Performance: Best results came from the SVM model paired with HOG features.
Pattern Discovery: Revealed useful land use patterns that could inform urban planning or environmental studies.
Transferable Techniques: Demonstrated how simple feature extraction + ML can be applied to problems like crop detection or mapping urban expansion.

Explore More: For a detailed exploration of the project’s methodology and findings, visit the GitHub repository: Land Cover Detection Project.

Programming Projects

Temperature Monitoring System

Objective: This project was inspired by time I spent in Sri Lanka, where I saw firsthand how factory workers often dealt with poor ventilation and extreme temperature swings caused by heavy machinery. I wanted to create a simple, affordable system that could help stabilize indoor conditions and improve day-to-day comfort on the factory floor.

Methodology:

Problem Focus: Build a simple, low-cost temperature monitoring and control system to help maintain a more comfortable environment for workers and improve overall productivity.
Hardware & Software: Used temperature and humidity sensors alongside a desktop application with a graphical user interface (GUI) to track real-time conditions and trigger alerts.
Programming & Visualization: Sensor data was visualized through live graphs showing trends throughout the day. A divide-and-conquer programming approach made the system modular and easy to maintain.
Solution Design: Proposed a basic feedback loop that used the sensor data to regulate environmental conditions automatically — with potential to activate fans or alerts based on set thresholds.

Key Outcomes:

Energy-Smart Design: The system can maintain optimal working temperatures across different shifts while reducing unnecessary cooling — saving energy and costs.
Worker Comfort & Focus: More stable conditions meant fewer productivity dips due to heat spikes, which workers reported positively during testing.
Live Monitoring & Alerts: Management could monitor readings from a single dashboard, set custom thresholds, and receive alerts to take action — no guesswork involved.
Contribution & Future Scope: This project can be scaled to support remote monitoring and more advanced automation. It’s a cost-effective blueprint for factories in similar climates looking to improve work conditions without large capital investments.

Explore More: Visit the project on GitHub for a comprehensive understanding of its development and functionality: Temperature Monitoring System

Programming Projects

Hydro-Power Allocation Optimization Model

Objective: To build a tool that helps energy planners understand how different hydro-power allocation decisions could affect job creation. The goal was to use data—not just assumptions—to support smarter policy and resource planning.

Methodology:

Model Development: I trained a decision tree regression model to predict the number of jobs generated based on power allocation levels across regions. This allowed for more targeted and outcome-driven energy planning.
Dashboard Build: To make the insights accessible, I created an interactive dashboard that let users input different allocation values and instantly see the projected impact on job creation.
Data Focus: The project leaned on publicly available economic and energy datasets to tie power distribution directly to employment projections.

Key Outcomes:

Predictive Insights: The model produced clear forecasts of job growth potential based on how hydro resources were distributed—helpful for planning both energy output and economic development.
Visual Clarity: The dashboard turned raw data into something usable and decision-friendly, especially for non-technical stakeholders.
Scalable Framework: While built around hydro-power, the same approach could be adapted to other resource allocation challenges—like budgeting, healthcare access, or education.
Contribution & Future Scope: This project showed how machine learning can translate technical data into actionable insights for public good. It was a hands-on exercise in combining predictive modeling with human-centered design to support smarter, more transparent decisions. Future iterations could expand to include multi-resource tradeoffs or deeper regional modeling.

Explore More: Visit the project repository on GitHub for detailed insights: Hydro-Power Allocation and Economic Impact Analysis on GitHub

Programming Projects

Research Network

Objective: Build a basic simulation of a researcher-focused social network, using object-oriented programming and data structures to handle user profiles, relationships, and intelligent connection recommendations.

Key Components:

- Profile Management System: Created a custom class to represent researcher profiles with details like name, email, research interests, and past experience.

- Data Structuring with BST: Used a Binary Search Tree to store and retrieve profiles efficiently, allowing quick lookup and alphabetical navigation.

- Graph-Based Connections: Designed a graph to simulate follower/following relationships between researchers and model their network structure..

- File Integration: Developed a file reader to import profile data from structured text files and populate the system automatically.

- Alphabetical Sorting Mechanism: Implemented a sorting mechanism to help users browse profiles in a structured, organized way.

- Follower Recommendations: Implemented a simple recommendation system using the triadic closure principle—suggesting new connections based on shared contacts.

Key Outcomes:

- Learned how to combine OOP, BSTs, and graphs into a cohesive tool that mirrors real-world systems like LinkedIn or ResearchGate.
- Practiced thinking in terms of data relationships, not just data points—crucial for systems that grow over time.
- The project showed potential for low-resource academic platforms that focus on discoverability, collaboration, and profile clarity.

Explore More: Visit the project repository on GitHub for detailed insights: Researcher’s Network on GitHub

What Clients Say

Testimonials

Samantha Connell

"Great to work with—clear communication and strong ROI"

Richard James

"Cut our ad costs and brought better leads"

Arion & Spiros

"Automated stuff we didn’t even know could be automated"

Gabriel Moschini

"The ads felt like they were made just for us"

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Email: chamithkotage@protonmail.com

Hi, I’m Chamith Practical AI Consulting Automation & Workflow Building Lead Generation Strategy

What I Do

My Portfolio

Consulting Projects

🟩 JamaicaWahGwaan ‘January Discount’ Campaign

🟦 33% Discount Campaign (Unique Health & Fitness)

🟪 Kefy Site Revamp

Programming Projects

Key Outcomes:

Testimonials

Samantha Connell

Richard James

Arion & Spiros

Gabriel Moschini

Contact With Me

Nevine Acotanza

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Hi, I’m Chamith
Practical AI Consulting Automation & Workflow Building Lead Generation Strategy