Freelance AI Automations in Nairobi

Freelance AI Automations in NairobiFreelance AI Automations in Nairobi

Projects People

proNairobi, Kenya

Turning your fintech and web3 ideas into shipped products

$50k+: Earned

45x: Hired

5.0: Rating

244: Followers

expert

expert

+2

Turning your fintech and web3 ideas into shipped products

Cover image for Codemechs - Revolutionizing the Tech Savanna

Codemechs - Revolutionizing the Tech Savanna

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Cover image for Complete Job Marketplace Platform

Complete Job Marketplace Platform

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243

Cover image for Fiberwave Website Redesign and SEO Migration

Fiberwave Website Redesign and SEO Migration

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Cover image for Epic Surf Discovery Platform Design

Epic Surf Discovery Platform Design

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AI Automation(2)

Victoria Tamara

AI & Automation Specialist | AI-powered Builder

5.0: Rating

13: Followers

AI & Automation Specialist | AI-powered Builder

Cover image for Personalized Lead Outreach Automation

Personalized Lead Outreach Automation

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Cover image for AI SEO Content Assistant

AI SEO Content Assistant

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Cover image for Automated Lead Engagement

Automated Lead Engagement

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Cover image for Shared group events and activities

Shared group events and activities are fun. Coordinating payments for them is not. Introducing Eventbit - a mobile app for planning shared group events and experiences, splitting costs, and collecting payments for future events without friction. ---- Group events can have a lot of friction when sharing costs, resources, event info and budgets. A good vacation or experience can also be quite expensive if made with one-off payments. Eventbit helps you split amongst friends AND automate payments collection for future events. Eventbit charges a 3% platform fee on each paid event. There is intentionally no subscription or monthly costs but the model scales effectively with usage: organizers only pay when their guests do, and groups only pay per event. Stripe powers the payment layer, including saved payment methods and automatic charges on scheduled installment due dates. ---- This is for you if: You, your friends, family, loved ones, and peers treasure novel shared experiences and would like to organize with ease. There's power in community and new experiences, and I hope that Eventbit helps more people spend time outside and together. ---- Built for the Bubble x Contra x Anthropic Hackathon. Branch version ID: mbogi (https://mbogi.bubbleapps.io/version-test/api/1.1/wf)

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129

AI Automation(3)

Ann Syombua Peter

Administrative Virtual Assistant | AI Automation of workflow

10: Followers

Administrative Virtual Assistant | AI Automation of workflow

Cover image for This week, I have been

This week, I have been working on automating my boss's inbox management, delegating email triage to AI while I handle reviews and approvals that require sound judgment. Because one wrong response to a client can cost a business revenue, I wanted to build a system that saves time without handing over critical decisions to AI. How I built it: I created two connected automation scenarios in Make.com (http://Make.com). Scenario 1: Intelligent Inbox Triage: AI analyzes incoming emails, categorizes them by priority, summarizes their content, and recommends the next action. This makes it easier to identify urgent messages and decide what needs attention first. Scenario 2: Human Review & Approval: The workflow supports the review and approval process before an email is sent. Slack notifications help bring relevant updates to my attention, so I can review the proposed action and approve the response before it goes out. Below are snippets of the two scenarios, including a Slack notification, showing how the workflow operates. My takeaway? AI can help manage the inbox, but when a response could affect revenue or a client relationship, the final decision should remain human.

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Cover image for AI-Powered Lead Follow-Up & Management

AI-Powered Lead Follow-Up & Management for Miale I automated lead follow-up and management for Miale to reduce the manual work involved in reviewing enquiries, categorizing leads, responding to prospects, and keeping the team informed. The problem: When leads come in, manually reviewing each response, deciding how to handle it, sending emails, and notifying the team can take time, and makes it easier for follow-ups to slip through the cracks. The solution: I built an AI-powered workflow in Make that automatically processes new lead submissions. Here’s how it works: Google Form → Google Sheets → AI Classification → Router → Email + Slack → Lead Tracking When a prospect submits the form, AI analyzes their collaboration interest and categorizes the lead as Collaboration Lead, Needs Follow-up, or Not Interested. The workflow then automatically: - Routes the lead based on their response. - Sends a relevant email to the prospect. - Notifies the team in Slack when a new lead needs attention. - Updates the lead record for easier tracking. Tools used: Make · Make AI Toolkit · Google Forms · Google Sheets · Gmail · Slack The workflow can also be adapted for client enquiries, sales leads, service requests, bookings, applications, and other repetitive lead-management processes. The goal isn't simply to automate tasks. It's to build a system that helps businesses respond faster, stay organized, and reduce manual follow-up work.

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Cover image for AI-Powered Gmail Inbox Assistant: Turning

AI-Powered Gmail Inbox Assistant: Turning Email Overload into an Organized Workflow A busy inbox can become a productivity problem. For a VA or business owner handling a high volume of emails, manually reading every message, deciding its priority, summarizing it, determining what action is needed, and organizing it takes time. And when everything sits in one inbox, important messages can easily get lost among routine notifications and newsletters. I built an automation to solve that problem. The Solution I created an AI-powered Gmail inbox assistant that captures, analyzes, organizes, and records incoming emails automatically. The workflow starts when a new email arrives in Gmail. New Gmail → AI analyzes the email → Information is recorded in Google Sheets → Zapier Paths route the email → Gmail label is applied The AI extracts useful information from each email, including: Priority – how urgently the email needs attention Email summary – a concise explanation of what the message is about Recommended action – what should be done next Service/category – used to determine how the email should be handled The information is then captured in a Google Sheet, creating a structured record that can be reviewed, tracked, and used for further workflows. From there, Zapier Paths use the classification to route the email to the appropriate action. For example: Urgent email → AI identifies the priority and summarizes the message → information is recorded in Google Sheets → Urgent Path runs → Gmail applies the Urgent label. WorkApp/Sites notification → AI identifies the category → details are recorded in Google Sheets → WorkApp/Sites Path runs → the corresponding Gmail label is applied. Newsletter → AI classifies and summarizes it → information is recorded in Google Sheets → Newsletter Path runs → the Newsletters label is applied. What Problem Does This Solve? This automation addresses several repetitive administrative tasks at once. Instead of manually opening emails, interpreting them, recording important details, and organizing them, the workflow handles the first layer of processing automatically. It helps create: Less manual sorting Emails are categorized automatically. Better visibility The Google Sheet provides a structured overview of incoming messages, their priority, summaries, and recommended actions. Faster prioritization Users can identify emails requiring attention without reading through the entire inbox first. A searchable record Important email information is captured in one place instead of remaining buried inside an inbox. How Businesses Can Use It The workflow can be adapted to different businesses and inboxes. For example, a company could create categories such as: Client enquiries | Leads | Support requests | Finance | Internal communication | Urgent | Newsletters The Google Sheet can then become a simple operational dashboard or the starting point for additional automations. For example, a business could later extend the workflow to: Urgent email → notify the responsible team member Client enquiry → create a lead in a CRM Follow-up required → create a task Support request → route to the appropriate team This makes the workflow more than an inbox organizer. It can become part of a wider business process automation system. Tools Used Gmail – captures incoming emails and applies labels AI by Zapier – analyzes and classifies email content Google Sheets – stores the email priority, summary, recommended action, and category Zapier Paths – applies conditional logic and routes emails based on their classification What This Project Demonstrates My approach to automation is simple: Find the repetitive problem first. Then build the system around it. This project started with a common administrative problem—too much email and too much manual sorting—and turned it into a workflow that can analyze information, structure it, make routing decisions, and trigger actions automatically. I'm building my skills in AI automation with a VA mindset: understanding the business problem first, then creating practical systems that reduce manual work and improve how information flows.

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Cover image for AI-Powered Client Enquiry Automation
Project Overview:
I

AI-Powered Client Enquiry Automation Project Overview: I built an AI-powered client enquiry automation workflow using Zapier, Google Forms, Google Sheets, AI by Zapier, Gmail, and Google Calendar. The goal was to automate the initial handling of client enquiries from receiving the enquiry to understanding the client's needs, sending an acknowledgement, and creating a follow-up task. The Problem: Managing client enquiries manually can be repetitive and time-consuming. Each new enquiry needs to be reviewed, categorized, summarized, responded to, and followed up. Without a structured process, it's easy for enquiries to be delayed or follow-ups to be missed. The Solution: I designed a workflow that automates these repetitive administrative tasks while using AI to analyze the information provided by the client. The automation follows this process: Client submits enquiry ↓ Google Sheets captures the enquiry ↓ AI analyzes the enquiry ↓ Gmail sends an acknowledgement ↓ Google Calendar creates a follow-up How It Works: 1. Enquiry Collection. The client submits their details and enquiry through a Google Form. The information is automatically recorded in Google Sheets. 2. AI Analysis. AI by Zapier reviews the enquiry and extracts key information such as the service category, priority, concise summary of the client's needs, and recommended next action. This eliminates the need to manually review every enquiry just to determine what it is about and how it should be handled. 3. Automated Client Response. After the enquiry is processed, Gmail automatically sends the client an acknowledgement, ensuring they receive a timely response. 4. Follow-Up Management. The workflow creates a Google Calendar follow-up, helping ensure that the enquiry doesn't get lost after the initial response. Result: The completed workflow turns a manual enquiry process into a structured automated system: Capture → Analyze → Respond → Follow Up The key improvement is the use of AI as a decision-making layer, rather than simply moving information from one application to another. This demonstrates how AI automation can reduce repetitive administrative work, improve response consistency, and help businesses stay organized with client enquiries. Tools Used: Zapier | AI by Zapier | Google Forms | Google Sheets | Gmail | Google Calendar Skills Demonstrated: AI Automation • Workflow Design • Administrative Automation • AI Prompting • Client Enquiry Management • Email Automation • Calendar Automation • Process Optimization

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1.3K

AI Automation(4)

Stephen Kisong'e

Cyber Security Analyst

Cyber Security Analyst

Cover image for AI-Assisted CTF Solving and Bug

AI-Assisted CTF Solving and Bug Bounty Hunting I integrated Cyber-Ornith Obliterated, an uncensored cybersecurity model running locally in LM Studio, with HexStrike AI through MCP to execute tools on Kali Linux. I demonstrated the setup by solving Root-Me’s HTML source-code CTF challenge. The model retrieved the page, inspected its HTML and identified a password exposed in a comment. I verified the command output and submitted the answer, successfully completing the challenge. Beyond CTFs, I built this project to support AI-assisted bug bounty hunting, including web response analysis and vulnerability investigation within authorized scope, with human oversight and verification of findings.

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Cover image for Designed and implemented a hands-on

Designed and implemented a hands-on AI red teaming environment using Microsoft PyRIT to evaluate the security of a local Retrieval-Augmented Generation application. The project connected a Parrot OS testing environment to a Windows-based AnythingLLM RAG application, with DeepSeek running locally through LM Studio. I configured PyRIT to communicate with the AnythingLLM workspace through a custom HTTP target and used controlled adversarial objectives to examine how the application handled requests involving financial records, customer information, payroll data, and restricted credentials. The testing workflow included API connectivity validation, isolated Python environment setup, automated prompt execution, response collection, and evidence review. The lab was built entirely around fictional Kiso Secure business data, allowing realistic sensitive-data disclosure scenarios to be tested without using real customer information or credentials. The resulting workflow demonstrates how automated AI red teaming can be used to identify potential data leakage, retrieval-boundary weaknesses, and unsafe handling of sensitive information in AI-powered applications.

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Cover image for Built a controlled Kiso Secure

Built a controlled Kiso Secure AI red teaming lab using Promptfoo to test a local RAG application for prompt injection, system prompt leakage, indirect prompt injection, and sensitive data exposure. The setup used AnythingLLM with a Kiso Secure knowledge base, automated adversarial testing, and a hardened workspace to compare security behavior before and after remediation.

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Cover image for Adversarial Data Poisoning Attack on a Network Intrusion AI Mod…

Adversarial Data Poisoning Attack on a Network Intrusion AI Mod…

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AI Automation(5)

Certified Bubble Developer helping founders launch powerful

Certified Bubble Developer helping founders launch powerful

Cover image for Flow Ledger – No-Code Finance

Flow Ledger – No-Code Finance MVP for Freelancers (Pre-Launch) Building Flow Ledger: the dashboard freelancers need to manage chaotic income with auto tax estimates, true per-client profit, and retirement planningall in one place. Flow Ledger auto-logs payments (Stripe-ready), deducts fees/taxes/retirement set-asides, and shows instant take-home. MVP progress: Live waitlist landing (free access) with signups from 30+ countries. Dashboard mocks: real-time take-home calculator, tax engine for 40+ countries, profitability breakdowns, retirement tracker with sliders & auto-adjustments. Built in Bubble.io (http://Bubble.io): dynamic workflows, global logic, dark-mode UI, multi-currency support. Waitlist momentum shows strong demand from freelancers tired of spreadsheets.

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Cover image for Easy Tiger is a branded

Easy Tiger is a branded fitness and wellness booking portal built on the Instabook platform, enabling clients to browse, book, and pay for yoga, pilates, and fitness classes both in-person and online. The platform handles class scheduling, live streaming, on-demand video hosting, and client management in one place. Key features built: — Class scheduling system with live and on-demand session support — Client self-service booking, cancellation, and rebooking available 24/7 — Integrated payment processing for class passes and subscriptions — Automated client re-engagement emails and promotional offers — Branded landing page with custom identity for Easy Tiger — Instructor and studio management dashboard Platform: Bubble.io (http://Bubble.io) / Instabook

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Cover image for Built and launched DeskHop.work (http://DeskHop.work)

Built and launched DeskHop.work (http://DeskHop.work) — a clean, modern platform that lets remote workers and digital nomads book coworking spaces and hot desks by the hour or day with zero commitment or membership. What I delivered: Real-time search and booking system (by location, date, and hours/days) Dynamic availability calendar Partner dashboard for coworking spaces to list desks and manage bookings Instant Stripe payments Clean, mobile-responsive design (works perfectly on iOS & Android) Scalable Bubble architecture with repeating groups, custom states, and background jobs Live Results: Now active in 30+ cities across 10 countries 45+ partner coworking spaces 200+ active users Tech: Bubble.io (http://Bubble.io) (full no-code development) Live link: https://deskhop.work/ This project shows how I turn complex booking logic into simple, user-friendly experiences that actually get used and generate revenue for both sides.

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Cover image for Rostered is an invite-only hospitality

Rostered is an invite-only hospitality hiring platform connecting employers with job seekers through a scrollable video feed. I was brought in as a Bubble developer to handle the full App Store submission and compliance process for the iOS mobile app built in Bubble Mobile Native. I resolved multiple Apple review rejections by fixing iOS permission strings, making signup fields compliant with Apple's data collection guidelines, updating the privacy policy and writing the business model clarification response to the Apple review team. The app is now live on the Apple App Store globally. 🔗 https://apps.apple.com/us/app/rostered/id6758422814

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AI Automation(2)

Brand Growth Partner | Social Media, Design, Video & Web

New to Contra

Brand Growth Partner | Social Media, Design, Video & Web

Cover image for 🤖 What if your business

🤖 What if your business had an AI agent that could actually get work done? This is how the AI agents and automation systems I build can work. From the moment information comes in, the agent can understand requests, access relevant knowledge, plan actions, connect with your business tools, automate workflows, manage data, communicate across channels, and deliver useful results. ⚡ Automate repetitive tasks 🧠 Maintain knowledge and context 🔌 Connect your business tools 📊 Manage and analyze data 💬 Support communication workflows 🌐 Perform web research and authorized browser tasks 🔄 Run scheduled and event-based workflows 🔐 Operate with controlled access and security The goal isn't just to add AI to your business. It's to build intelligent systems that help your business work smarter. I'm now building custom AI agents and business automation systems for businesses, startups, agencies, and entrepreneurs. If you have a repetitive workflow, manual process, or business task that takes too much time, let's explore how AI and automation can help. 🚀 Custom AI Agent & Business Automation #AIAgents #AIAutomation #ArtificialIntelligence #BusinessAutomation #WorkflowAutomation #Automation #AIIntegration #BusinessTechnology #DigitalTransformation

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Cover image for URÉLIA Luxury Fragrance Campaign

URÉLIA Luxury Fragrance Campaign

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1

Cover image for Long-form YouTube videos and Shorts,

Long-form YouTube videos and Shorts, edited start to finish. This project shows my range across two formats: in-depth long-form videos built to hold attention, and fast-paced Shorts built to grab it in the first second. My role: Video Editor What I did: Long-form: Cut raw footage and narration into a clear, engaging story. I tightened pacing, added B-roll and visuals, synced music and sound effects, and used smooth transitions and on-screen text to keep viewers watching. Shorts: Reworked content into vertical, high-energy clips with strong hooks, dynamic captions, quick cuts, and sound design made for mobile viewers. Added subtitles, sound mixing, and color correction so every video looks polished and consistent. Skills and tools: Premiere Pro, CapCut, After Effects, DaVinci Resolve Focus: Storytelling, pacing, and audience retention. Need your videos edited like this? Message me or hire me directly. I deliver on time, include revisions, and can adapt to your channel’s style.

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Built the Brand Presence of r/design_critiques, from 30 to 5.4K Weekly Visitors r/design_critiques is a community that helps new and amateur designers improve their work through honest, constructive critique. Over 2 months, I shaped how the brand shows up on Reddit: its voice, its culture, and its content. That took the subreddit from 30 to 5.4K weekly visitors. Brand work behind the growth: Defined a welcoming, feedback-first tone of voice for the community Set the standards for how critiques are given, so the brand stayed consistent and beginner-friendly Created recurring content formats that made the community recognizable Moderated daily to protect the brand’s culture and reputation Tracked weekly stats and refined content based on what resonated Results: 30 → 5.4K weekly visitors in 8 weeks 490 weekly contributions 444 post karma and 566 comment karma

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AI Automation(1)

Applied AI Engineer — AI Agents, RAG & Automation

Applied AI Engineer — AI Agents, RAG & Automation

Cover image for Currently building autonomous AI systems

Currently building autonomous AI systems that actually survive production — not just the demo. Most AI projects work beautifully in a controlled test and then quietly fall apart on real data, edge cases, and concurrency. I focus on the unglamorous engineering that closes that gap: data validation pipelines, boundary checks, error handling, and knowing exactly where deterministic logic should own the decision instead of the model. Recent work includes agentic workflows built with Python and FastAPI, an LLM reasoning layer for the genuinely ambiguous decisions, and automation orchestrated through Make with MCP. My background is technical support and operations, which means I design for the failure case first — I've spent years watching systems break in ways their builders never anticipated. If you have an AI pilot that impressed everyone in the demo and then stalled on the way to something dependable, that gap is exactly what I build for. Open to Applied AI / AI automation projects.

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Cover image for Support Logic Analyzer — Michael Limisi

Support Logic Analyzer — Michael Limisi

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Cover image for Support Engineering Simulation Platform

Support Engineering Simulation Platform

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Cover image for AI-Powered Knowledge Base Pipeline Development

AI-Powered Knowledge Base Pipeline Development

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AI Automation(1)

AI Agents l AI Automation l Make.com l N8N

AI Agents l AI Automation l Make.com l N8N

Cover image for AI Lead Classifier for Sales Optimization

AI Lead Classifier for Sales Optimization

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Cover image for AI Proposal Generator for Fast Proposal Turnaround

AI Proposal Generator for Fast Proposal Turnaround

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Cover image for Message Classification Automation for Lead Scoring

Message Classification Automation for Lead Scoring

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AI Automation(2)