You will get AI PoC Development for SaaS, Automation, Chatbots, and Internal Tools
Rising Talent
Rising Talent
Project details
What sets me apart in PoC development is that I do not build a PoC just to “show something working.” I build it to answer the most important risk question before you spend more money on full development.
Many PoCs look nice but do not prove enough. They avoid the hard part, use clean demo data, or only show a happy path. Then later, the real build fails when messy inputs, API limits, user edge cases, or business rules appear.
My approach is to first identify the riskiest assumption. Can the AI produce reliable output? Can the workflow be automated? Can the API integration actually support the use case? Can users get value from this flow? Then I build a focused PoC around that specific question, with enough backend, AI logic, automation, and testing to prove whether the idea is worth taking forward.
I have built production AI systems using LLMs, RAG, voice AI, n8n, CRM integrations, dashboards, and custom backend logic. For a PoC, my goal is simple: validate the core idea fast, expose the technical risks early, and give you a clear path for the MVP instead of letting you waste budget on assumptions.
Many PoCs look nice but do not prove enough. They avoid the hard part, use clean demo data, or only show a happy path. Then later, the real build fails when messy inputs, API limits, user edge cases, or business rules appear.
My approach is to first identify the riskiest assumption. Can the AI produce reliable output? Can the workflow be automated? Can the API integration actually support the use case? Can users get value from this flow? Then I build a focused PoC around that specific question, with enough backend, AI logic, automation, and testing to prove whether the idea is worth taking forward.
I have built production AI systems using LLMs, RAG, voice AI, n8n, CRM integrations, dashboards, and custom backend logic. For a PoC, my goal is simple: validate the core idea fast, expose the technical risks early, and give you a clear path for the MVP instead of letting you waste budget on assumptions.
AI Algorithms
CycleGAN, Generative Adversarial Network, Large Language Model, Long Short-Term Memory Network, Multilayer Perceptron, Multimodal Large Language Model, Recurrent Neural Network, Self-Organizing Map, Transformer Model, YOLOAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI-Enhanced Medical Imaging, AI-Generated Music, Automatic Speech Recognition, Conversational AI, Image Recognition, Natural Language Generation, Natural Language Understanding, Object Localization, Speech SynthesisAI Development Language
PythonAI Tools
Azure OpenAI, Bing AI, GitHub Copilot, Gradio, Hugging Face, Microsoft 365 Copilot, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlowAI Models
BERT, ChatGPT, DALL-E, GPT-4, LaMDA, LLaMA, Midjourney AI, Naive Bayes Classifier, OpenAI Codex, WhisperWhat's included $500
These options are included with the project scope.
$500
- Delivery Time 5 days
- Number of Revisions 2
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About Kamran
Full-Stack AI Engineer | AI Automation, AI Agents, RAG & SaaS MVPs
100%
Job Success
Lahore, Pakistan - 9:27 am local time
My work covers the complete product lifecycle: AI strategy, system architecture, backend development, frontend development, LLM integration, RAG pipeline development, vector database setup, API integration, cloud deployment, testing, and iteration.
Recent production work includes a $15K+ AI SaaS platform used by active users, including AI voice agents, RAG document intelligence, real-time analytics, authentication, Stripe billing, admin dashboards, role-based access, and cloud deployment.
What I build:
• AI Agents & AI Workflow Automation
Custom AI agents, workflow automation systems, internal automation tools, customer support bots, lead qualification agents, appointment booking agents, CRM automation, sales automation, operations automation, and multi-step LLM workflows.
• RAG Systems & Document Intelligence
RAG chatbots, knowledge base assistants, PDF Q&A systems, document search tools, internal company AI assistants, citation-based answers, vector search, secure document retrieval, Pinecone, Chroma, Weaviate, LangChain, and LlamaIndex.
• Voice AI Agents
Inbound voice agents, outbound voice agents, AI receptionists, call handling systems, appointment booking automation, lead qualification calls, customer support voice bots, phone workflow automation, Vapi, Retell AI, ElevenLabs, Deepgram, and OpenAI voice workflows.
• AI SaaS & MVP Development
Launch-ready AI SaaS products and MVPs with authentication, Stripe billing, subscriptions, user dashboards, admin panels, analytics, role-based access, REST APIs, databases, and cloud deployment.
• Full-Stack Web Application Development
Scalable full-stack applications using Python, FastAPI, Django, Node.js, Express.js, React, Next.js, TypeScript, Tailwind CSS, PostgreSQL, MySQL, MongoDB, Redis, Docker, AWS, and cloud infrastructure.
AI / LLM stack:
OpenAI API, Claude, Gemini, LangChain, LlamaIndex, Pinecone, Chroma, Weaviate, vector databases, embeddings, prompt engineering, RAG pipelines, LLM orchestration, AI agent development, API integrations, and automation workflows.
I have worked across healthcare, legal tech, logistics, e-commerce, HR, education, real estate, and service businesses, especially where teams need to automate customer support, document review, booking, reporting, lead management, internal search, CRM workflows, or operational processes.
How I work:
I help you clarify what is feasible, identify technical risks early, avoid overbuilding, and ship the version that reaches users and revenue fastest. You get clear communication, honest timelines, clean execution, and production-focused development.
If you are building an AI agent, AI automation system, RAG chatbot, voice AI agent, LLM app, SaaS platform, or MVP, send me your use case and I’ll help you map the fastest practical path to a production-ready version.
Steps for completing your project
After purchasing the project, send requirements so Kamran can start the project.
Delivery time starts when Kamran receives requirements from you.
Kamran works on your project following the steps below.
Revisions may occur after the delivery date.
Idea & Feasibility Review
I review your idea, target use case, required AI behavior, data sources, and success criteria.
PoC Development
I build the AI proof of concept with the required workflow, UI, backend, and integrations.