Freelancers using Next.js in ObrenovacFreelancers using Next.js in Obrenovac
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Engjell Developer's avatar
Engjell Developer
proBelgrade, Serbia
Software Developer | CO FOUNDER at Aligator.xyz
5.0
Rating
43
Followers
Software Developer | CO FOUNDER at Aligator.xyz
Cover image for Helloouu there, do you find
Helloouu there, do you find this website attractive www.furnishot.com
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Cover image for Just built a voice interactive
Just built a voice interactive orb with Three.js 🔮 First time experimenting with it, this was fun as hell. Would love some feedback from the Contra fam.
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Cover image for After 5+ years… I finally killed my 2019 portfolio 😂 Just l...
After 5+ years… I finally killed my 2019 portfolio 😂 Just launched the new one this weekend: www.engjell.dev (http://engjell.dev) Clean, fast, and has a 3D cartoon me because I thought it was funny. Let me know what you think (honest feedback welcome)! Currently open for new projects if anyone needs a new site 🚀 #webdeveloper #portfolio #tailwind #nextjs
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Cover image for Guys, I tried blending modern design with nature… what do yo...
Guys, I tried blending modern design with nature… what do you think? luxholz.ch (http://luxholz.ch)Website for wood flooring company in Swiss 🇨🇭
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Next.js(9)
Darko Tokanovic's avatar
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 designed and developed the
I designed and developed the operating layer behind a family of AI phone receptionists. The voice conversation is only the customer-facing surface. This platform gives business owners and administrators the tools required to understand, control and improve what happens during real telephone calls. The system supports multiple specialized workspaces, including dental practices, veterinary clinics, hair salons and beauty businesses. Each workspace has isolated services, staff, schedules, business information, appointment rules and agent instructions. Key capabilities include: • Centralized call and project overview • Call recordings and complete transcripts • Structured call summaries and extracted caller intent • Appointment status and outcome tracking • Service, staff and schedule administration • Business hours, pricing, promotions and knowledge management • Transfer and escalation configuration • Email confirmations and appointment management links • Voice, web, database and recording health monitoring • Web and React Native administration • Separate business workspaces on one shared architecture I developed the backend APIs, database models, administrative interfaces, authentication, email workflows, monitoring, deployment and integration with the real-time voice services. This project demonstrates that the system is more than an AI voice demo. It includes the operational controls, review workflow and verified action tracking required for real business use. This is an independently developed product, not a paid client project.
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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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Next.js(1)
Filip Mijic's avatar
Filip Mijic
Obrenovac, Serbia
AI Automation & Integration Engineer — n8n, AI Agents, RAG
New to Contra
AI Automation & Integration Engineer — n8n, AI Agents, RAG
Cover image for AI resume builder with RAG
AI resume builder with RAG chat — shipped to production, $0 recurring infra. I design and build lean, production-grade AI products. My latest, kairesume (live at kairesume.fit (http://kairesume.fit)), tailors resumes to any job description, scores ATS keyword match, drafts cover letters, and answers user questions through a retrieval-augmented chat assistant grounded in real product docs — so it stays accurate. What I bring to your project: RAG systems — pgvector, embeddings, chunking, retrieval that doesn't hallucinate Full-stack AI apps — Next.js 14 + TypeScript, Supabase, Groq/LLM integration, streaming chat Cost-efficient architecture — I shipped this whole system on a $0 infra budget by making sharp tradeoffs Production workflow automation — n8n ingestion pipelines If you need an AI feature built right — RAG chat, document tooling, or an LLM-powered MVP — let's talk. Available for freelance and contract work now.
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Cover image for Multi-Agent Orchestrator Development
Multi-Agent Orchestrator Development
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Cover image for An open-source Python RAG app.
An open-source Python RAG app. Documents (PDF/DOCX/MD/TXT) are loaded, split into paragraph-aware overlapping chunks, embedded, and stored in a ChromaDB vector store. At query time the question is embedded, the closest passages are retrieved via cosine top-K search, injected into a grounding-and-refusal system prompt, and the answer is streamed back with its source chunks shown. LLM and embedding providers are pluggable (Groq/OpenAI and local sentence-transformers/OpenAI) via .env, and it ships with both a Streamlit UI and a CLI. An evaluation harness measures retrieval hit-rate and answer accuracy on a labelled Q/A set.
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Cover image for Automated RAG vector store sync
Automated RAG vector store sync (n8n + Supabase pgvector) The problem: a retrieval-augmented chatbot whose knowledge base drifts out of date the moment the source docs change — unless someone remembers to manually re-embed everything. What I built: a fully automated reindex pipeline in n8n that keeps the vector store current with zero manual steps. How it works: Triggers on a daily schedule and on a deploy webhook Fetches source markdown, chunks it on heading boundaries with overlap to preserve context Embeds in batches via a Supabase Edge Function (384-dim) Bulk UPSERTs vectors into Postgres with pgvector Removes stale chunks from deleted or shortened docs automatically Why it's solid: Idempotent — safe to re-run any number of times, no duplicates, no drift Runs entirely on free tiers ($0 infra) Retry-on-fail on network calls + a dedicated error workflow for alerts I design and ship production automations like this — RAG pipelines, data sync, internal tooling, and API integrations. If you're building anything with AI retrieval or you've got a repetitive data process worth automating, send me a message and let's scope it.
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Next.js(1)
Momcilo Popov's avatar
Momcilo Popov
Belgrade, Serbia
Design engineer & developer for 15+ years
5.0
Rating
3
Followers
Design engineer & developer for 15+ years
Cover image for Some design & layout animation
Some design & layout animation explorations from a recent project
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Cover image for videotoflip.com
videotoflip.com
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4
Cover image for landing page development i did
landing page development i did
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Cover image for TB to one of the
TB to one of the funniest projects've ever built
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Next.js(2)
Vladimir Babic's avatar
Vladimir Babic
Belgrade, Serbia
🚀 Design, Webflow, Next js and Hedless commerce
🚀 Design, Webflow, Next js and Hedless commerce
Cover image for Swiss Master Data Management
Swiss Master Data Management
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Cover image for Howdy Health
Howdy Health
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55
Cover image for 360 Workx Branding
360 Workx Branding
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29
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Next.js(1)
Predrag Gagović's avatar
Predrag Gagović
Belgrade, Serbia
Full-Stack Dev | AI, Blockchain & Cloud Solutions
8
Followers
Full-Stack Dev | AI, Blockchain & Cloud Solutions
Cover image for Custom AI chatbot
Custom AI chatbot
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Cover image for Anomaly Detection and Analysis
Anomaly Detection and Analysis
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Cover image for Stock price app
Stock price app
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Cover image for Stock price app
Stock price app
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Next.js(1)