Freelancers using Django in GujaratFreelancers using Django in Gujarat
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Zillion Infotech's avatar
Zillion Infotech
Surat, India
Building technology that creates real business impact.
5.0
Rating
1
Followers
Building technology that creates real business impact.
Cover image for BenchMark ◆ Context & Challenge The client
BenchMark ◆ Context & Challenge The client needed a modern and scalable digital platform to showcase services, support marketing campaigns, and improve client engagement. The challenge was to combine high-performance web development with UX-driven design and integrated marketing tools, while enabling businesses to track performance and optimize their digital presence effectively ◆ Approach & Solution We developed a user-centric digital platform that integrates design, content, and marketing capabilities, enabling businesses to manage their online presence and drive data-driven growth. ◆ Key focus areas: ‣ User-centric UI/UX for improved engagement ‣ SEO and performance marketing integration ‣ Content-driven architecture for scalability ‣ Analytics and conversion tracking systems ‣ Secure and high-performance infrastructure ◆ Execution ‣ Built responsive and scalable web platform ‣ Implemented SEO and content management capabilities ‣ Integrated analytics tools for user behavior tracking ‣ Developed UX testing and usability optimization workflows ‣ Designed secure hosting and performance-focused architecture ◆ Outcome & Impact The platform enables businesses to enhance their digital presence and optimize marketing performance. ‣ Improved user engagement through optimized UX design ‣ Increased visibility with integrated SEO strategies ‣ Data-driven decision making with analytics insights ‣ Enhanced conversion rates through performance optimization ‣ Scalable foundation for ongoing digital growth
0
77
Cover image for ZonVids: Video creating platform ◆ Context
ZonVids: Video creating platform ◆ Context & Challenge: The client needed a scalable platform to help eCommerce brands create high-converting video content for their product listings. The challenge was to connect brands with relevant creators, streamline content production, and ensure fast delivery of quality videos that improve conversion rates and visibility on marketplaces like Amazon. ◆ Approach & Solution: We developed a creator marketplace platform that enables brands to discover, collaborate with, and manage influencers and content creators for producing UGC and live video content. ◆ Key focus areas: ‣ Marketplace for connecting brands with video creators ‣ UGC and influencer-based content production workflows ‣ Integration with eCommerce platforms like Amazon ‣ Fast turnaround for video creation and delivery ‣ Scalable system for managing campaigns and creators ◆ Execution: ‣ Built platform for onboarding brands and creators ‣ Developed campaign workflow for video production and delivery ‣ Implemented creator discovery and selection system ‣ Created integration flows for Amazon listings and content usage ‣ Designed scalable backend for managing multiple campaigns ◆ Outcome & Impact: The platform enables brands to boost product visibility and conversions through engaging video content. ‣ Increased conversion rates with video-enabled listings ‣ Simplified creator collaboration and campaign management ‣ Faster content production with streamlined workflows ‣ Improved product visibility across marketplaces ‣ Scalable solution supporting growing brand and creator network
0
80
Cover image for Claimcow ◆ Context & Challenge The client
Claimcow ◆ Context & Challenge The client needed a digital platform to simplify and automate the insurance claims process for users. The challenge was to reduce manual effort, improve claim success rates, and create a transparent system where users can easily submit, track, and manage their claims without complex procedures or delays. ◆ Approach & Solution We developed an automated claims management platform that streamlines the end-to-end claims process, from submission to resolution, using structured workflows and intelligent data handling. ◆ Key focus areas: ‣ Simplified claim submission and tracking experience ‣ Automated workflows for claim processing ‣ Transparent status updates and communication ‣ Secure handling of sensitive user and claim data ‣ Scalable system for managing multiple claim types ◆ Execution ‣ Built end-to-end claims submission and tracking system ‣ Developed workflow engine for claim processing automation ‣ Implemented user dashboard for real-time claim status ‣ Created secure infrastructure for handling sensitive data ‣ Designed scalable backend to support high claim volumes ◆ Outcome & Impact The platform enables users to manage insurance claims efficiently with minimal friction. ‣ Reduced complexity in claim submission process ‣ Improved transparency with real-time tracking ‣ Increased efficiency through workflow automation ‣ Enhanced user experience with simplified interface ‣ Scalable solution supporting growing user base
0
75
Cover image for Antidote- Healthcare  ◆ Context & Challenge The
Antidote- Healthcare  ◆ Context & Challenge The client needed a scalable digital healthcare platform to provide affordable and accessible medical services through a virtual-first model. The challenge was to deliver reliable, real-time telehealth services while ensuring data security, clinical accuracy, and seamless patient-doctor interactions across web and mobile platforms. ◆ Approach & Solution We developed an AI-powered telehealth platform that enables patients to access medical care, connect with clinicians, and manage their health digitally through a unified and secure system. ◆ Key focus areas: ‣ AI-assisted patient screening and clinical decision support ‣ 24/7 access to virtual healthcare services ‣ Seamless video consultation and communication workflows ‣ Integrated system for appointments, prescriptions, and records ‣ Scalable and secure healthcare infrastructure ◆ Execution ‣ Built telehealth platform for real-time video consultations ‣ Developed AI-driven symptom screening and support systems ‣ Implemented patient management for appointments and records ‣ Created secure infrastructure compliant with healthcare standards ‣ Designed scalable architecture for continuous care and access ◆ Outcome & Impact The platform enables patients to access quality healthcare services anytime, anywhere, at an affordable cost. ‣ Improved access to primary and urgent care services ‣ Reduced healthcare costs through virtual-first approach ‣ Enhanced patient experience with seamless digital interactions ‣ Enabled continuous care for chronic and preventive health needs ‣ Scalable solution supporting growing patient demand
0
71
Django(4)
Jaykumar Parmar's avatar
Jaykumar Parmar
Surat, India
Expert in React Js | NextJS | MERN| FE| BE | AI | Node Js
5.0
Rating
18
Followers
Expert in React Js | NextJS | MERN| FE| BE | AI | Node Js
Cover image for Wope - React/Python SEO analytics platform
Wope - React/Python SEO analytics platform
2
237
Cover image for Grace | InsurTech | React | Frontend
Grace | InsurTech | React | Frontend
1
31
Cover image for SkinnyRx | Healthcare | React | Frontend
SkinnyRx | Healthcare | React | Frontend
1
39
Cover image for AI Chat Interface Development
AI Chat Interface Development
1
28
Django(1)
Rajanit Navapara's avatar
Rajanit Navapara
Gujarat, India
Web Dev, Canva Designer & Photo Editor Pro
Web Dev, Canva Designer & Photo Editor Pro
Cover image for BgRemover
BgRemover
0
7
Cover image for Quiz Game Web
Quiz Game Web
0
10
Cover image for Nutter Joy Peanut Butter (@nutterjoy_) • Instagram photos and v…
Nutter Joy Peanut Butter (@nutterjoy_) • Instagram photos and v…
0
4
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Django(2)
Parv Gatecha's avatar
Parv Gatecha
Ahmedabad, India
Passionate Software Engineer and AI Developer
Passionate Software Engineer and AI Developer
Cover image for Network- Twitter clone
Network- Twitter clone
0
14
Cover image for Arbiter — AI Trust &
Arbiter — AI Trust & Evaluation Platform Arbiter is an enterprise-grade AI trust and evaluation platform built to help teams test, secure, monitor, and govern LLM-powered applications before and after they reach production. Modern AI applications can fail in ways that traditional software testing does not easily catch. A prompt change can reduce answer quality, a model upgrade can introduce regressions, an agent can expose sensitive information, or a jailbreak can bypass application-level safeguards. Arbiter provides an infrastructure layer for continuously evaluating and controlling these systems. Core Capabilities LLM Evaluation Automated evaluation of LLM responses against configurable criteria. Support for deterministic and statistical evaluation workflows. Compare different models, prompts, and configurations. Track quality changes across evaluation runs. Statistical analysis using techniques such as the Mann–Whitney U test and bootstrap confidence intervals. Adversarial Testing Test LLM applications against jailbreaks, prompt injection, adversarial prompts, and other failure scenarios. Create repeatable attack suites for regression testing. Run security and reliability checks before deployment. AI Firewall & Policy Engine Acts as a control layer between applications and LLM providers. Inspect prompts and model responses. Apply configurable policies to block, modify, or flag potentially unsafe requests and responses. Provide centralized enforcement rather than implementing safety logic independently in every application. Memory Protection Analyze information being written to or retrieved from AI memory. Apply policies around sensitive information and potentially unsafe memory operations. Reduce the risk of unintended persistence of confidential information. CI/CD Quality Gates Integrate AI evaluation into the software delivery pipeline. Automatically evaluate model or prompt changes before deployment. Fail a deployment when configurable quality, safety, or regression thresholds are not met. Treat AI behavior as something that can be tested continuously rather than manually reviewed after deployment. Observability Track AI requests, responses, evaluation results, policy decisions, and failures. Designed around OpenTelemetry for integration with existing observability infrastructure. Provides visibility into how AI systems behave in real-world usage. Architecture Arbiter is designed as an infrastructure layer around existing AI applications rather than requiring teams to rebuild their applications from scratch. Application → Arbiter Gateway → Policy & Security Layer → LLM Provider Requests can pass through evaluation, policy enforcement, security checks, and observability before reaching the underlying model. Responses can then be evaluated and monitored before being returned to the application. This architecture allows teams to introduce AI governance without tightly coupling their application to a specific model provider. Engineering Focus The project combines: LLM evaluation Statistical testing Adversarial AI security AI governance API gateways Policy engines Memory security CI/CD automation Observability Production AI infrastructure The goal is to move LLM applications from “it works in a demo” toward systems that can be continuously tested, monitored, and controlled in production.
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33
Cover image for MNIST
MNIST
0
8
Cover image for Movie Recommendations
Movie Recommendations
0
6
Django(1)
Harsh Kishorani's avatar
Harsh Kishorani
Godhra, India
I build smart devices and the apps that run them
I build smart devices and the apps that run them
Cover image for Smart Gym Management Platform Development
Smart Gym Management Platform Development
1
16
Cover image for Hand Gesture-Controlled RGB Lighting System
Hand Gesture-Controlled RGB Lighting System
1
14
Cover image for Development of Zen Text Editor
Development of Zen Text Editor
1
10
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Django(1)
Param India's avatar
Param India
Vadodara, India
Tech dreams. Pioneered.
Tech dreams. Pioneered.
Cover image for PADC Management System
PADC Management System
0
6
Cover image for Uchat Global
Uchat Global
0
5
Cover image for PADC Transit
PADC Transit
0
4
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Django(2)
DHANRAJ SHARMA's avatar
DHANRAJ SHARMA
Mehsana, India
AI Automation Specialist — I build AI workflows that ship
New to Contra
AI Automation Specialist — I build AI workflows that ship
Cover image for Full-stack AI road trip planner
Full-stack AI road trip planner that computes the cheapest fuel-stop strategy for any US route. Built using Django REST API, React, Mapbox, and a custom optimization algorithm. Deployed live on Vercel + Render.
1
213
Cover image for I build custom AI-powered contract
I build custom AI-powered contract analysis web applications that help users review contracts, identify risks, and generate clear recommendations in minutes. Using LangChain, RAG, Llama models, Hugging Face embeddings, Flask, and Docker, I create production-ready solutions that can analyze PDFs, DOCX files, and text documents, detect risky clauses, generate plain-English summaries, and provide structured risk scores. Perfect for LegalTech startups, law firms, procurement teams, HR departments, and founders looking to automate contract review workflows. Includes source code, deployment, customization, and post-launch support.
0
60
Cover image for Built SiteScope AI, an AI-powered
Built SiteScope AI, an AI-powered client intake and discovery call automation system using Make.com (http://Make.com), Google Gemini AI, Jina AI Reader, Tally, Google Sheets, Google Calendar, Gmail, and Google Meet. The system automatically processes client submissions, extracts and analyzes website content, generates business insights, creates discovery call strategy briefs, produces personalized recommendations, schedules meetings with automatic calendar invites, sends branded confirmation emails, and logs all data into a structured CRM. The automation eliminates manual pre-call research, scheduling, and follow-ups while enabling faster lead response times and fully prepared discovery calls within minutes of form submission.
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69
Cover image for Developed ReviewRadar, an AI-powered customer
Developed ReviewRadar, an AI-powered customer review monitoring and business intelligence system built with n8n, Google Gemini AI, SERPAPI, Google Sheets, Gmail, Slack, Twilio WhatsApp, and Looker Studio. The platform continuously collects Google Reviews, classifies sentiment, identifies complaint categories, assigns urgency scores, generates AI-powered response drafts, and instantly notifies stakeholders of critical feedback. Weekly executive summaries and interactive dashboards provide actionable insights into customer sentiment, review trends, top complaints, top praise, and business performance. The automation eliminates manual review monitoring while enabling proactive reputation management and faster customer response times.
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187
Django(1)