Freelancers using Twilio

Freelancers using TwilioFreelancers using Twilio

Projects People

proLagos, Nigeria

Full-Stack Engineer | Replit Expert | Mobile Dev

$25k+: Earned

65x: Hired

4.9: Rating

104: Followers

Expert

Expert

Full-Stack Engineer | Replit Expert | Mobile Dev

Cover image for Development of Bite Club CRM Platform

Development of Bite Club CRM Platform

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Cover image for Sea League Website Redesign & Development

Sea League Website Redesign & Development

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Cover image for Beezy Mobile App Development

Beezy Mobile App Development

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Cover image for MentorMePreK – Childcare LMS for Preschools & Daycares

MentorMePreK – Childcare LMS for Preschools & Daycares

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Sebastian Avelar

proParis, France

AI-First App Developer | Claude, Supabase, n8n

$10k+: Earned

14x: Hired

5.0: Rating

145: Followers

expert

AI-First App Developer | Claude, Supabase, n8n

Cover image for Bubble-based Healthcare Web Application Development

Bubble-based Healthcare Web Application Development

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Cover image for Hey! I just shared a

Hey! I just shared a write-up on something I learned while rebuilding a product with AI agents:) The main idea is pretty simple: Don’t put all your product context in one giant agent file. Keep the main file small, and put the real product knowledge inside structured docs that the AI can navigate when it needs them. This has helped me a lot when working on a SaaS product with a lot of business logic! Sharing the full breakdown here: https://docswarp.notion.site/How-to-document-your-product-so-AI-can-actually-build-it-3c09678204c580948a52c0f4ec86d6fc?source=copy_link I'm offering consulting services to set this up! :)

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1.5K

Cover image for If you have Bubble app and you need an MCP for either: - con...

If you have Bubble app and you need an MCP for either: - connect it to Claude, ChatGPT, or others - Integrate the OpenAI Agent builder that can interact with your backend - Use chatkit from OpenAI, etc I built: https://bubble-mcp.com/ using Replit! I'll be sharing more guides on how to use this tool and the type of experiences you can create with it :) I created the design using Figma Make and then connected Figma MCP to Replit to provide a clear idea of how the UI should be. Love Figma Make :)

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869

Cover image for Improving MyHomies: A Modern Housing Marketplace in Switzerland

Improving MyHomies: A Modern Housing Marketplace in Switzerland

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Islamabad, Pakistan

Full-stack developer building high-impact web products.

$25k+: Earned

3x: Hired

5.0: Rating

52: Followers

Full-stack developer building high-impact web products.

Cover image for 1-800-FlyFish

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Cover image for AX3 Sonic – Your Podcast Hub for Teams & Audiences

$14K+ earned

AX3 Sonic – Your Podcast Hub for Teams & Audiences

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Cover image for Shopify Store Customization Based on Figma Designs

Shopify Store Customization Based on Figma Designs

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Cover image for Fractional Property Ownership Web App

Fractional Property Ownership Web App

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Darko Tokanovic

Belgrade, Serbia

AI voice agents that answer calls and book appointments

New to Contra

AI voice agents that answer calls and book appointments

Cover image for I built a workflow that

I built a workflow that turns a business website into a testable AI phone receptionist. The system analyzes the website, extracts services, staff, opening hours, policies, and other relevant information, then creates an isolated voice-agent demo for that business. Instead of sending a generic recording, we can provide a real phone number that allows the business to test the agent through an actual call. When the website or scheduling system supports an integration, the agent can check availability and book appointments during the call. Otherwise, it safely captures the caller’s details and preferred time for staff follow-up. If a business decides to continue after the demo, the same foundation can be expanded into a production receptionist with databases, customer-specific business rules, calendar and CRM integrations, confirmations, call summaries, analytics, and administrative controls. The extracted information can also reveal gaps in the business website. Its content and structure can then be improved so both visitors and the AI receptionist receive clearer, more reliable information. The main lesson I share is that website extraction alone is not enough. Information must be normalized, validated, and restricted to the source material before it can be used safely in a live voice conversation. The demonstration uses a fictional dental clinic and real recordings from my working voice-agent system. No patient data, real customer information, or invented testimonials are included. I used Descript to assemble and refine the presentation, edit the narration and real-call sections, create captions, and prepare the final submission.

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Cover image for I designed and developed a

I designed and developed a specialized AI phone receptionist for veterinary clinics. The system handles real PSTN and SIP calls through FreeSWITCH. It combines streaming speech recognition, LLM orchestration and low-latency voice synthesis to communicate naturally with pet owners. The agent can answer questions about veterinary services, business hours, location, parking and clinic policies. It can identify the pet owner’s reason for calling, distinguish routine appointment requests from potentially urgent situations, check configured availability and guide the caller through a veterinary visit request. The system includes: • Real US telephone and SIP call handling • Pet-aware reason-for-visit collection • Routine, sick-visit and urgent-request routing • Veterinary service and provider information • Appointment booking, rescheduling and cancellation flows • Email confirmations and owner notifications • Safe escalation for urgent or unresolved situations • Call recordings, transcripts and structured summaries • Appointment status and administrative review • Configurable services, staff, schedules, policies and instructions • Replaceable speech recognition, LLM and voice providers I developed the telephony architecture, real-time conversational pipeline, backend APIs, veterinary call flows, appointment logic, email integration, administration, deployment and real-call testing. The agent does not diagnose animals or replace veterinary judgment. Urgent, uncertain or clinically sensitive requests are handled according to configured escalation rules. This is an independently developed product, not a paid client project.

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Cover image for I designed and developed Anna

I designed and developed Anna Dental AI, a specialized phone receptionist for dental practices. The system answers real PSTN and SIP calls through FreeSWITCH and combines streaming speech recognition, LLM orchestration and low-latency voice synthesis to hold natural telephone conversations. Anna can answer questions about dental services, expected price ranges, business hours, providers and clinic policies. It can identify the requested treatment, match the caller with an appropriate provider, check configured availability and guide the caller through an appointment request. The system also includes: • Real US telephone and SIP call handling • Dental service and provider matching • Price, hours, location and policy questions • Appointment booking, rescheduling and cancellation flows • Email confirmations and appointment management links • Safe escalation for unresolved or sensitive requests • Call recordings, transcripts and structured summaries • Appointment status and administrative review • Configurable services, staff, schedules and agent instructions • Replaceable speech recognition, LLM and voice providers I developed the telephony architecture, real-time voice pipeline, backend APIs, appointment workflows, email integration, web administration, deployment and testing. The agent is designed for administrative communication and scheduling. It does not provide diagnoses or replace professional clinical judgment. This is an independently developed product, not a paid client project.

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Cover image for I designed and developed a

I designed and developed a specialized AI phone receptionist for hair and beauty salons. The system answers real telephone calls, explains salon services and prices, identifies the requested treatment, handles appointment requests and sends email confirmations. It uses FreeSWITCH and SIP telephony with streaming speech recognition, LLM orchestration and low-latency voice synthesis. The agent supports natural interruptions and is optimized for telephone-quality audio. I also built business-specific service matching and confirmation logic. During real-call testing, phrases such as “men’s haircut” produced several transcription variants, so the system uses aliases, conversational context and confirmation rules instead of relying on a single raw transcript. The management layer provides call recordings, transcripts, summaries, appointment status and configurable information such as services, staff, prices, opening hours, promotions and agent instructions. My responsibilities included telephony architecture, backend development, AI orchestration, appointment workflows, email integration, administration, deployment and real-call testing. This is an independently developed product, not a paid client project.

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Founder of Kazfen | AI Agents, SaaS & Automation

New to Contra

Founder of Kazfen | AI Agents, SaaS & Automation

Cover image for Kazfen Lead Capture Engine —

Kazfen Lead Capture Engine — AI Intake System for Roofing Contractors Built the lead intake layer powering Kazfen’s AI pipeline. The system captures homeowner requests, structures job data, and feeds the AI engine for qualification, prioritization, routing, and follow-up automation. Captured signals include roof type, urgency, location, insurance status, inspection timing, and service request details. Features: • Roofing-specific lead intake flow • Structured AI-ready data capture • Contractor routing logic • Qualification pipeline trigger system • AI enrichment preparation • Downstream automation workflows • Lead-to-agent architecture This intake layer powers the entire Kazfen automation stack from lead submission to qualification, scoring, SMS workflows, and contractor actions. Stack: FastAPI • PostgreSQL • Claude • Twilio • Stripe

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Cover image for Kazfen Contractor Command Center —

Kazfen Contractor Command Center — AI-Prioritized Roofing Pipeline Built the operational dashboard contractors use daily to manage leads, inspections, follow-ups, and revenue opportunities. The system continuously analyzes incoming leads, prioritizes urgent opportunities, drafts actions, and surfaces what needs attention first. Features shown: • AI Morning Briefing (“do this first”) • Lead prioritization + urgency scoring • Pipeline value + expected revenue tracking • AI-generated recommendations and actions • Lead lifecycle management (new → booked → won) • Contractor review workflows • Natural-language command interface (“Ask Kazfen”) • Roofing-specific intelligence and revenue insights Kazfen acts as an AI operations layer rather than a traditional CRM. Stack: FastAPI • PostgreSQL • Claude • Twilio • Stripe • Render

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Cover image for Kazfen — AI Lead Intelligence

Kazfen — AI Lead Intelligence & Qualification Engine for Roofers Built and deployed a production AI platform for roofing contractors that captures leads, scores opportunities, qualifies jobs, estimates value, drafts follow-ups, and prioritizes next actions automatically. Features shown: • AI lead enrichment + scoring • Insurance detection + urgency analysis • Estimated job value intelligence • Contractor assignment workflows • AI recommendations + next actions • Voice pipeline + SMS automation • Production SaaS deployment Stack: FastAPI, PostgreSQL, Twilio, Claude, Stripe, Render.

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Cover image for Kazfen — AI Roofing Operating

Kazfen — AI Roofing Operating System Built and launched Kazfen, an AI-first operating system for roofing contractors. Kazfen automatically qualifies inbound leads, prioritizes opportunities, drafts follow-ups, generates morning briefings, scores pipeline value, and helps contractors run their business from anywhere. Features include: • AI voice qualification + lead intelligence • Contractor dashboard + pipeline analytics • AI SMS drafting and inbox workflows • Morning briefing + next-action engine • Voice-controlled pipeline system • Lead scoring + estimated job value prediction • TCPA safety layer, audit trail, dry-run mode, security stack Stack: FastAPI + PostgreSQL + Claude + Twilio + Stripe + Render Built end-to-end as founder and engineer.

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AI Agent Engineer | Voice agents, automations & integrations

New to Contra

AI Agent Engineer | Voice agents, automations & integrations

Cover image for Inbound AI Voice Agent, Configured

Inbound AI Voice Agent, Configured in GoHighLevel (Plus a Custom Agent in Our Own Dialer) I built an inbound AI voice agent in GHL that answers the client's number. It greets the caller, works the conversation from a script with built-in objection handling, and books or routes the call based on how it goes. Every call writes back to the CRM: contact record, opportunity stage, timeline note. The team sees exactly what happened on every call without touching a thing. No new software to learn, it's configured in the CRM they already run on. And when a client needs the outbound side, I've built that too. A custom AI voice agent from the pipeline up. Pipecat with OpenAI Realtime, speech to text, LLM, text to speech, all in a single WebSocket, embedded right into our own power dialer. A sales team dials prospects in parallel and hands the conversation to the AI: script, objection handling, voicemail branch, and the outcome written straight back to the CRM. The whole pipeline is covered by a 91-case automated test suite, and if the AI service goes down, the call degrades gracefully instead of crashing. Inbound on GHL, outbound in our dialer. Same voice AI capability, in the shape the client's workflow needs.

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Cover image for Compliance-Aware Email + SMS Follow-Up

Compliance-Aware Email + SMS Follow-Up Automation. A sales team was making cold calls and losing the follow-up. Leads that asked to be contacted later had no reliable path back into the funnel, and the team had no way to guarantee they were respecting opt-in rules. I built a follow-up automation that handles the timing and the compliance in one system. The workflow triggers when a call ends with a follow-up disposition, then runs a 3-day timed sequence of email and SMS touches. Before any message goes out, the system checks the contact's opt-in status, and any contact on the blacklist is skipped entirely. Follow-ups only ever go to people who asked for them. Every step is visible in the CRM timeline, so the team can see exactly where each lead is in the sequence, and a human can take over at any point without breaking the flow. It turns "we'll follow up" from a promise into a guarantee, without adding another manual task to the day.

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Cover image for I build custom Power Dialer with Parallel Calling and CRM In...

I build custom Power Dialer with Parallel Calling and CRM Integration

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Cover image for I built this follow-up workflow

I built this follow-up workflow in GoHighLevel for a holistic health practice running cold outreach. When a lead gets called, the workflow captures the call outcome and runs a condition check for opt-in status and blacklist before anything sends. My approach: a 3-day email + SMS sequence with timed branches, one touch per day. Day 1 opens the conversation, Day 2 delivers value, Day 3 closes with a booking link. I added blacklist handling so opted-out contacts never receive another message, which keeps the practice compliant and the sender reputation clean. The result: every called lead gets a consistent, no-touch follow-up cadence, so the practice stays top-of-mind without any manual work from the team.

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Rawalpindi, Pakistan

Full Stack Engineer|AI Calling Agent|Web| Twilio

Full Stack Engineer|AI Calling Agent|Web| Twilio

Cover image for AI Chatbot for Customer Support

AI Chatbot for Customer Support

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Cover image for "Crafting Dynamic Twilio IVR & AI Calling Solutions"

"Crafting Dynamic Twilio IVR & AI Calling Solutions"

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Cover image for Audio Transcription and Call Summary Using OPEN.AI Chat GPT.

Audio Transcription and Call Summary Using OPEN.AI Chat GPT.

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Cover image for Elevating Businesses through Expert Web Development Services

Elevating Businesses through Expert Web Development Services

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Custom Software, AI & SaaS Built for Business

New to Contra

Custom Software, AI & SaaS Built for Business

Cover image for SiteFlow Daily lets field crews

SiteFlow Daily lets field crews document a shift in under two minutes: what got done, what is unfinished, what the next crew needs to know, photos, issues, and milestone updates. Those entries feed a visual project timeline and roll up into project and portfolio dashboards for managers and executives. It supports simple single-timeline jobs and complex multi-trade projects with trade-specific milestones and completion rollups. Issues can be flagged and routed to responsible contacts, and reports export to PDF and CSV. An AI layer cleans up field notes and drafts summaries without inventing official records.

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Cover image for RoundRobin Dial OS places high-volume

RoundRobin Dial OS places high-volume parallel outbound calls to opted-in leads and instantly routes every live, human-answered call to an available agent. Dial volume is a computed value — the minimum of human capacity, campaign ceilings, answer-probability budget, routing capacity, abandonment budget, provider limits, and compliance gating — never a raw admin input. Managers get a live sales-floor control tower and admins a command center for teams, campaigns, numbers, compliance, and analytics. It is compliance-aware by design with consent tracking, opt-out management, call-window rules, and audit trails.

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Cover image for Admins add unique assets and

Admins add unique assets and quantity-based inventory and generate QR codes. Field workers scan or search an item, check it out, and assign it to a job, crew, vehicle, person, or location, recording condition and a due date, then check it back in with return condition. The dashboard shows what is available, checked out, overdue, damaged, lost, or low in stock, and every asset carries an immutable history timeline. It includes role-based access, alerts, reports, and CSV import/export, and stays simple enough to use from a phone in seconds.

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Cover image for Admins add employees, employees submit

Admins add employees, employees submit PTO requests, and each request appears in an inbox and notifies the assigned manager. Managers approve or deny in the app or through secure one-time approval links sent by email, the decision is recorded, and the employee is notified. A calendar shows who is off and when, and the app tracks simple PTO balances, conflict warnings against departments, blackout dates, and holidays, minimum-notice rules, settings, and CSV reports. It is deliberately scoped to stay a simple approval tool rather than a full HR platform.

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