Freelance AI Agent Designers in India

Freelance AI Agent Designers in IndiaFreelance AI Agent Designers in India

Projects People

proBengaluru, India

Product Designer • Mobile & Web • Motion Design • AI • SaaS

$50k+: Earned

17x: Hired

5.0: Rating

1.1K: Followers

Top

expert

+12

Product Designer • Mobile & Web • Motion Design • AI • SaaS

Cover image for Agency Landing Page Design with AI Tools

Agency Landing Page Design with AI Tools

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70

Cover image for Mobile App Compilation - AI Agent Taste

Mobile App Compilation - AI Agent Taste

5

117

Cover image for Website design project for an architecture firm

$1.5K+ earned

Website design project for an architecture firm

48

1K

Cover image for Art Gallery Mobile App Design for Bidd'me - FinTech

Art Gallery Mobile App Design for Bidd'me - FinTech

26

733

AI Agent Designer(2)

Product studio for startups, apps, dashboards, and AI.

$25k+: Earned

8x: Hired

5.0: Rating

55: Followers

expert

Product studio for startups, apps, dashboards, and AI.

Cover image for Autonomous AI SEO Agent for Sabai Health

Autonomous AI SEO Agent for Sabai Health

2

0

29

Cover image for PotatoBook: Designing a Budgeting App People Don't Avoid

PotatoBook: Designing a Budgeting App People Don't Avoid

1

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14

Cover image for Solika Arts: Multi-Portal SaaS Platform for an Art School

Solika Arts: Multi-Portal SaaS Platform for an Art School

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1

19

Vaulta: Brand Identity for a Fintech Wealth Platform

1

21

AI Agent Designer(1)

proChandigarh, India

Building AI-Powered, Web & Mobile Applications | Full-Stack

5.0: Rating

38: Followers

Building AI-Powered, Web & Mobile Applications | Full-Stack

Cover image for We recently built an AI

We recently built an AI Customer Support Agent, and one thing surprised us... The chatbot wasn't the hardest part. Getting the AI to understand the business was. The quality of an AI assistant isn't determined by the model alone. It's determined by the information you give it. During development, we found that connecting the AI to the right documentation, FAQs, business rules, and workflows made a far bigger difference than switching between models. Once the AI had the right context, responses became more accurate, consistent, and genuinely helpful. It reinforced something we've been seeing across recent AI projects: Businesses don't need another chatbot. They need an AI assistant that actually understands their business. That's where the real value is. Curious to see how other teams are approaching AI knowledge management. What's been your biggest challenge when building AI products? #AI #ArtificialIntelligence #CustomerSupport #AIAgents #SaaS #ProductDevelopment #Automation #OpenAI #Claude #BusinessAI #TvaronTechnologies

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4

286

Cover image for Turn More Leads into Customers

Turn More Leads into Customers with AI Sales CRM Growing a business is more than collecting leads it's about nurturing the right opportunities and closing deals faster. An AI-powered Sales CRM helps your team work smarter by automating repetitive tasks and providing actionable insights. At Tvaron Technologies, we build intelligent AI Sales CRM solutions that help businesses streamline sales, improve customer relationships, and accelerate growth. Key Features: 🤖 AI Lead Scoring 📈 Sales Pipeline Management 📧 Email & Follow-up Automation 👥 Contact & Customer Management 📊 Real-Time Sales Dashboard 🔔 Smart Reminders & Notifications 🔗 CRM & Third-Party Integrations 📱 Web & Mobile Applications Whether you're a startup or an enterprise, our custom AI CRM solutions are designed to boost productivity, improve conversions, and help your sales team focus on what matters most closing deals. Build a smarter sales process with Tvaron Technologies. #AISalesCRM #CRM #ArtificialIntelligence #SalesAutomation #LeadManagement #BusinessGrowth #CustomerRelationshipManagement #DigitalTransformation #BusinessAutomation #CustomSoftware #WebDevelopment #MobileAppDevelopment #EnterpriseSoftware #Startup #Innovation #Technology #TvaronTechnologies #SoftwareDevelopment #AI #SalesTech

2

4

931

Cover image for Ai Agents for Daily Business

Ai Agents for Daily Business Needs

1

1

148

Cover image for ProjectLinq: Sports Court Construction Management Platform

ProjectLinq: Sports Court Construction Management Platform

1

1

AI Agent Designer(3)

UX & Service Designer crafting human-centered systems

9: Followers

UX & Service Designer crafting human-centered systems

Cover image for I design. I build. I

I design. I build. I ship. Figma → Framer → production. No handoffs or back and forth. Just a finished product. Roy Studio has 2 spots this month. If you know, you know. If you don't—royflows.com (https://—royflows.com)

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161

Cover image for Mainframe is a conceptual AI

Mainframe is a conceptual AI studio — brand system + full multi-page website, built entirely in Stitch. Landing page with animated states, five inner pages (Labs, Studio, Services, Openings), and a complete DESIGN.md (http://DESIGN.md) covering color, type, and layout. Monochromatic, editorial, cinematic. The kind of system that usually takes weeks — done in one session. Started with brand tokens, used them as the foundation for every page. Iterated hover states and animations without leaving the design context. The generated DESIGN.md (http://DESIGN.md) became the actual handoff doc. Fastest I've gone from concept to a coherent multi-page system. Want: auto-propagating token updates across pages, finer motion controls, native multi-page navigation. Otherwise — best design-gen tool I've used since Figma got auto-layout.

7

9

463

Cover image for Just wrapped a custom store

Just wrapped a custom store build and I'm genuinely proud of this one. Minimal. Clean. The kind of ecommerce experience that doesn't shout—it just works. Product pages that breathe. A checkout flow so smooth it almost feels intentional. Collections that actually make sense when you're browsing. The hero hits different when you scroll through it live. Real product imagery. Real storytelling. The whole vibe just clicks. This is what I build for brands that know design matters. No template defaults. No generic flows. Just a store that converts because it feels right. Demo's ready to show—thinking this could be something special for the right founder. → DM if you're building something like this.

1

85

Cover image for I set a quick design

I set a quick design challenge for myself: What would a high-end landing page look like for a national defense contractor or a private drone dealer? 🚁🔥 Check out my latest UI/UX concept: a cinematic, dark-mode experience for a next-gen tactical drone called "The Executioner." The goal was to blend intense military aesthetics with a sleek, minimalist tech UI. Let's hear your thoughts in comments!

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97

AI Agent Designer(5)

Greater Noida, India

UI/UX Designer • No-code Builder • AI Architect

$1k+: Earned

64: Followers

expert

UI/UX Designer • No-code Builder • AI Architect

Cover image for I built something wild for

I built something wild for the Paper Challenge🚀 It turns any GitHub repo into a visual case study — instantly. No writing. No designing. Just drop a repo link… and the canvas builds itself. That’s CodeSage💯 Most devs have solid projects… but they’re buried in README files nobody reads. CodeSage changes that. It reads your actual code — architecture, stack, commits — and transforms it into a clean, dark, presentation-ready case study. The real unlock? Paper MCP. I connected my AI agent directly to the canvas. So instead of designing manually… the agent builds everything: • Sections • Layout • Insights • Structure All generated directly on the canvas. No drag. No drop. Just output. Pick any repo → get 3 analysis modes: *Each one gives → Complexity score → PR velocity → Language breakdown → Full Refactor Roadmap Try CodeSage: https://codesage-871524277866.us-central1.run.app/ Tech stack: Paper MCP · Gemini API · GitHub API · Antigravity

22

58

1.2K

Cover image for Finding freelance clients shouldn't take

Finding freelance clients shouldn't take hours. Prospectra is a Notion agent that hunts leads for you, scores them by priority, and writes your cold emails — automatically. → Finds real leads from across the web → Tells you who to reach out to first → Writes personalised cold emails instantly → Keeps your entire pipeline inside Notion Stop scrolling LinkedIn for hours. Try it → https://www.notion.so/agent/3357b509492d801682d200929fc20ce0 Let AI fill your pipeline.

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7

329

Cover image for AI Trading Co-Pilot reimagines how

AI Trading Co-Pilot reimagines how humans interact with financial data. Instead of overwhelming dashboards, the interface introduces an AI presence that observes, analyzes, and responds in real time. When a user selects a cryptocurrency, the AI activates — scanning price movement and liquidity signals through a cinematic analysis sequence before delivering a clear risk level and strategic suggestion. https://ai-trading-co-pilot.figma.site/ The core innovation lies in the interaction: A responsive AI panel that feels alive Smooth state transitions from observation to insight Subtle ambient motion that creates a futuristic, intelligent atmosphere Built entirely in Figma Make, this prototype explores a new design language for collaborative decision-making — where AI acts as a co-pilot, not an autopilot.

5

322

Cover image for I wanted to make a

I wanted to make a photography website that felt more like an experience than a portfolio. So I built CINÉRA (https://cinera-app.lovable.app) — a cinematic photography studio website with a 3D gallery, interactive archive, real availability, and a complete booking flow. You can explore the work, pick a date and time, add your shoot details, and get booked without the usual back-and-forth. On the studio side, there’s a dashboard to manage bookings and inquiries, plus automatic booking confirmations to take a bit of the repetitive work off the photographer’s plate. This was built for an appointment-based business challenge, and honestly, I had way too much fun making it.

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17

872

AI Agent Designer(3)

Web developer ,UI/UX and logo designer!!!!

New to Contra

Web developer ,UI/UX and logo designer!!!!

Cover image for Paws & Purrs is an ultra-luxurious,

Paws & Purrs is an ultra-luxurious, boutique boarding sanctuary designed exclusively for cats. Built with a high-end, minimal editorial aesthetic, the website highlights the premium experience offered to feline guests—including private architectural accommodations, gourmet dining, daily spa grooming, and interactive play sessions. Every detail of the stay is tailored around a cat's natural rhythms and uncompromising veterinary-grade safety standards, providing owners with absolute peace of mind while they are away.

1

337

Cover image for Atelier is a high-end, ultra-premium

Atelier is a high-end, ultra-premium web experience built for a luxury kitchen design and architecture studio. The core goal of the project was to move away from standard web layouts and create a deeply immersive, cinematic journey that wows users from the very first pixel.

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308

Cover image for GLITCH is a premium, futuristic luxury

GLITCH is a premium, futuristic luxury sportswear landing page designed to deliver a high-end, cinematic user experience. Rather than a traditional e-commerce layout, it acts as one continuous, highly interactive editorial magazine spread.

1

305

Cover image for Beyond Coaching - Website Overview
This

Beyond Coaching - Website Overview This website is a premium, modern landing page built for Beyond Coaching, a personal growth and coaching platform. It is designed to create a strong, cinematic first impression using modern web design principles.

2

287

AI Agent Designer(14)

AI Systems & Security Engineer | AI Agents, RAG & Automation

AI Systems & Security Engineer | AI Agents, RAG & Automation

Cover image for Case Study 2: Zero Trust

Case Study 2: Zero Trust Gateway Cybersecurity Zero Trust Architecture Project: Zero Trust Gateway — Identity-Aware Access Control and Continuous Verification Problem Traditional network security often relies on trusted internal networks. However, remote access, compromised credentials and vulnerable devices can expose sensitive applications and data. Proposed Solution A Zero Trust Gateway that verifies every access request using identity, device health, contextual information and access policies before granting access to protected resources. System Architecture Access request: An employee, external user or AI agent requests access. Identity verification: Authenticate the user's identity through an identity provider. Device verification: Check device security status and compliance. Policy engine: Evaluate access permissions, location and risk signals. Access control: Grant limited access or deny the request. Continuous monitoring: Log activity and detect suspicious behavior. Technology Stack Python and FastAPI OAuth 2.0 / OpenID Connect PostgreSQL Redis Docker Policy-based access control Key Features Identity-based authentication Least-privilege access Device posture verification Context-aware access policies Centralized audit logs Session monitoring and revocation Practical Example An employee attempts to access an internal HR application from a remote laptop. The gateway verifies the employee's identity. It checks whether the device meets security requirements. The policy engine confirms the employee belongs to the HR team. If all requirements are satisfied, access is granted only to the HR application. Suspicious activity can trigger additional verification or access revocation. Expected Outcome A security gateway that reduces unauthorized access and limits the potential impact of compromised accounts or devices. Real-world applications Enterprise networks Cloud infrastructure Remote employee access API security AI agent access control Project Impact The gateway demonstrates how identity, device trust and access policies can work together to protect modern applications. Conceptual case study; security effectiveness requires implementation, penetration testing and validation.

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Cover image for Case Study 1: AgentTape
AI Engineering
Agent

Case Study 1: AgentTape AI Engineering Agent Observability Project: AgentTape — AI Agent Execution Recording, Replay & Debugging System Problem AI agents perform multiple tasks using LLMs, APIs, databases and external tools. When an agent produces an incorrect result or fails, identifying the exact cause can be difficult. Proposed Solution AgentTape is a Python-based observability system that records AI agent executions and allows developers to replay and debug them. System Architecture Input: Receive a task from the user. Agent execution: The AI agent reasons, calls tools and processes data. Recording: AgentTape captures tool calls, inputs, outputs, errors and execution events. Replay: Developers review previous executions step by step. Evaluation: Compare different runs to identify failures and improve performance. Technology Stack Python LangChain and LangGraph PostgreSQL and JSON Docker LLM APIs Key Features Complete execution tracing Step-by-step replay Error detection and debugging Agent performance evaluation Execution history and analytics Expected Outcome A reusable observability layer that helps developers understand agent behavior, troubleshoot failures and improve the reliability of AI applications. Real-world applications AI customer support agents Autonomous research agents AI workflow automation Enterprise AI systems Project Impact AgentTape aims to make complex AI agent workflows more transparent, traceable and easier to maintain. Conceptual case study; performance improvements require implementation and testing.

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Cover image for Stateful Multi-Agent Recruitment CRM —

Stateful Multi-Agent Recruitment CRM — Case Study The Challenge Recruitment loses quality through context loss. Resume parsing, scoring, outreach, follow-ups, and scheduling are separate workflows. Agents don't share candidate state → conflicting messages, duplicate follow-ups, missed scheduling windows. The Solution LangGraph multi-agent orchestrator with 5 specialized agents + shared persistent memory. Agent breakdown: Parser Agent → Extract skills, experience, fit signals from resumes Scoring Agent → LLM-based ranking (not rule-based scores) Outreach Agent → Generate personalized LinkedIn/email messages Follow-up Agent → Handle multi-touch cadence, track responses Scheduling Agent → Book interviews, avoid conflicts Critical architecture: Shared AgentState All agents read/write to the same state → no context switching. The Positioning Headline: "AI agents that handle end-to-end recruitment workflow — from resume to interview." Value props: "Stateful" → Agents don't repeat work; they know what happened to each candidate "Multi-Agent" → Specialized agents → better performance than monolithic LLM "End-to-End" → Parse → Score → Outreach → Follow-up → Schedule (no manual handoffs) Metrics They Lead With Metric Result Candidates Processed 500+ Time Saved 70% Qualified Candidates 3x more Workflow Fully Automated Mini case study in the image: Input: 500 candidate applications Parse: Extract info automatically Score: Rank candidates (50% filtered out) Outreach: AI-generated, personalized messages Follow-up: Automated multi-touch Result: 3x more qualified candidates reach interview Dashboard UX Right panel shows: Candidates list with: Score (92, 78, 65), Status (Qualified, Contacted, Follow-up), Next Action, Last Update AI-Generated Outreach sample → Shows quality of personalization (candidate name, specific role match) Interview Scheduling → Visual calendar, slot selection UX insight: Dashboard surfaces actions (Send outreach, Schedule call), not just metrics. Tech Stack (Why It Matters) LangGraph → Agent orchestration + state management (core to stateful workflows) PostgreSQL → Persistent candidate state (not ephemeral) FastAPI → Scalable API layer Redis → Cache for scoring/matching LLMs (OpenAI/Claude) → Parsing, scoring, outreach generation Why this stack wins: Agents can be tested independently (Scoring Agent accuracy measured separately) State persists across failures (retry-safe) Scalable to 1000+ parallel workflows What You Should Copy 1. Architecture Don't build a monolithic "recruitment AI." Build 5 focused agents, each optimized for one task. Let LangGraph manage the handoffs. 2. State Management The shared AgentState is the moat. Without it: Outreach Agent doesn't know candidate was already contacted Scheduling Agent double-books Follow-up Agent sends duplicate messages Action: If building recruitment or SDR automation, design shared state first. Agents second. 3. Positioning Shift RudraStack: "Automate follow-ups" (feature-first) This system: "End-to-end workflow" (outcome-first) + "Stateful agents" (technical credibility) Result: Attracts technical buyers (CTOs, engineering orgs) + recruiters who care about quality. 4. Metrics Hierarchy Output quality (3x more qualified candidates) Time saved (70%) Volume (500+ processed) Most tools lead with volume. This leads with quality first. Competitive Edge for Your Stack vs. RudraStack: RudraStack: Dashboard-first, lead quantity focus This system: Agent-first, candidate quality focus vs. Traditional ATS: Stateful agents = no lost context LLM-driven scoring = learns from outcomes Multi-agent = modular and debuggable Technical Differentiation You Could Build Agent fine-tuning → Specialized models for Parser/Scoring agents (better accuracy than GPT-4 for resume parsing) Feedback loop → Track which outreach messages → interviews → placements. Retrain Outreach Agent. Multi-source orchestration → LinkedIn sources + Career portal sources + Referrals, all in shared state Real-time scoring updates → As follow-up responses come in, re-score candidates (dynamic ranking) Quick Tactical Win for Your AI-SDR Apply this to your staffing agency outreach: Replace your SDR follow-up system with a Follow-up Agent that reads shared candidate state Add a Conversation Analysis Agent that scores email replies (Intent: Interested? Unsubscribe? Dead-end?) Route high-intent replies to Scheduling Agent automatically Result: 3x faster sales cycle because context isn't lost between touch points.

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Cover image for RudraStack AI Recruiting System —

RudraStack AI Recruiting System — Case Study The Challenge Staffing agencies lose placements through manual follow-up bottlenecks. Sales teams qualify 128 leads/week but convert only 18% to interviews and 8% to placements. Each follow-up is friction. The Solution RudraStack automated the qualification → follow-up → placement workflow with a funnel-focused dashboard that surfaces three metrics: Lead quality score (Screen phase) Follow-up cadence (Automate phase) Close velocity (Close phase) The Positioning Tagline: "Screen. Follow Up. Close." Value prop stack: "Qualify Better Leads" (lead scoring, not volume) "Automate Follow-Ups" (remove manual scheduling friction) "Close More Placements" (optimize handoff to sales) Metrics They Led With Week-over-week growth (vs. absolute numbers): New Leads: +24% Follow-Ups Sent: +31% Interviews Booked: +18% Placements Made: +27% Dashboard KPIs: 128 → 87 → 42 → 28 → 23 (transparent funnel decay) Why This Works Funnel transparency — Agencies see where they leak (87→42 is biggest drop = qualification problem) ROI-first messaging — "Placements Made" as headline metric, not efficiency scores Growth narrative — Week-over-week % (not flat counts) creates urgency Speed as trust signal — "2-Minute Overview" reduces time-to-value perception What You Should Copy Lead with the result metric (placements/closes), not the process (leads screened) Show funnel stages visually so clients can diagnose their own bottleneck Use week-over-week %, not absolute numbers, for acquisition copy Dashboard-first positioning (not API/integration first) Competitive Angle for Your Stack If you're building against RudraStack: Differentiate on: LinkedIn-native workflows (vs. dashboard upload), higher qualification accuracy (vs. volume automation), or lower cost Own what they gloss over: What's the actual qualification logic? Why does 87→42 leak? Better LLM-based scoring?

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AI Agent Designer(4)

Bengaluru, India

Product designer building AI + UX experiences

New to Contra

Product designer building AI + UX experiences

Cover image for AI Agent onboarding and responses

AI Agent onboarding and responses for support channels 🚀 I worked on multi-workspace integration with AI agent onboarding in Slack for Freddy AI Agent, enabling organizations with multiple Slack instances to seamlessly connect and manage their workflows. Also, I enhanced conversational AI capabilities, designing interactions that felt more natural, contextual, and engaging for employees. Together, these enhancements made Freddy more scalable and adaptive for enterprise collaboration, while driving measurable improvements in employee experience, productivity, and trust in AI-driven support. Conversational AI with Streaming Responses 🙌 - To make interactions feel more natural and human-like, I designed conversational flows where Freddy AI streams responses in real time, instead of showing a static block of text. This design reduces waiting anxiety, keeps users engaged, and mirrors the way people chat with colleagues. Alongside streaming, I worked on improving response text to be more empathetic, clear, and context-aware. The focus was on striking a balance between brevity and enough detail to solve the user’s problem while maintaining a conversational, approachable tone. The outcome: smoother, engaging conversations that not only help users find solutions faster but also build trust in the AI as a reliable support companion.

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Cover image for Product Insights AI Agent and

Product Insights AI Agent and MCP Servers Designed an automated Weekly Product Review Pulse that transforms public App Store and Google Play reviews into a concise one-page insight report for fintech products. The system clusters review feedback, surfaces recurring themes, pulls representative quotes, and highlights actionable ideas to help teams quickly understand customer sentiment. Reports are delivered through Google Workspace using MCP servers for Google Docs and Gmail, keeping the workflow structured, repeatable, and easy to share. I used Cursor to build the workflow end-to-end, from structuring the review pipeline to refining the automation logic. To keep the system modular, I created a separate MCP server in GitHub to handle the Google Docs and Gmail draft automation independently. This allowed me to generate the report in Docs, prepare the email draft in Gmail, and keep the workflow clean, reusable, and easy to maintain. Open the case study here: https://www.chitragohad.com/growwaiagent

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Cover image for YAMRAJ Pre-Workout - Social media

YAMRAJ Pre-Workout - Social media campaign Created a complete AI-powered visual campaign for Kaizen Energy’s YAMRAJ Pre-Workout, transforming a single product image into a cohesive set of high-impact marketing assets. What I worked on: - Developed the visual concept and art direction - Created cinematic product advertising compositions - Designed AI-generated gym lifestyle scenes - Created 3D billboard / Times Square-style advertising concepts - Developed ingredient-explosion and product hero visuals - Created an Instagram carousel campaign with 7 individual posts - Built a consistent visual language across product, lifestyle, and social creatives - Used AI image generation to explore multiple advertising directions - Focused on strong product visibility, dramatic lighting, motion-inspired compositions, and brand consistency Creative direction: Neon green + yellow palette, dark gym environments, high-energy VFX, fruit and gummy elements, cinematic lighting, bold typography, and a gritty fitness aesthetic. Deliverables: Product posters • Lifestyle ads • 3D billboard concept • Ingredient visuals • Instagram carousel • Social media creatives Tools: AI image generation, visual art direction, graphic design, product advertising & social media design.

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Cover image for Email Design Template
Project Overview
Designed a

Email Design Template Project Overview Designed a personal-brand email newsletter to share milestones, services, free resources, and drive users toward a 1:1 booking. Objective Create an email that communicates personal and business milestones, builds credibility through social proof, highlights useful design resources, and promotes paid services without making the email feel overly promotional; encourages readers to book a 1:1 session My Role: Email UX + Visual Design I worked on the content hierarchy, layout, visual system, responsive structure, and CTA placement to create an email that is easy to scan and works across desktop and mobile. Design Approach 1. Strong narrative flow The email moves from: Introduction → Problems → Social proof → Resources → Services → CTA → Closing The opening immediately frames the user's problem around resumes and portfolios before introducing the solution. 2. Social proof as a credibility layer The 91+ bookings milestone and most-booked service appear early to build trust before asking users to take action. 3. Modular content blocks Different sections are visually separated into reusable modules for achievements, data, free templates, and the Topmate profile. This makes the email easier to scan and easier to adapt for future campaigns. 4. Clear visual hierarchy Large editorial-style headings, contrasting backgrounds, iconography, and short content blocks help users quickly understand each section. The visual system uses a dark green, mint, and lavender palette with Georgia/Arial typography. 5. Responsive-first structure The template includes responsive behaviour that stacks multi-column sections on smaller screens, helping preserve readability on mobile.n. Outcome: Created a reusable, responsive email template that combines storytelling, credibility, resource sharing, and conversion into one cohesive experience. The template can be adapted for future newsletters, personal-brand updates, product announcements, or service promotions. https://canva.link/email-designs

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AI Agent Designer(2)