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I will build a full stack rag ai web application
Talal N.
About this gig
Need a production-ready RAG AI web application, not just a basic chatbot?
I build full-stack AI applications with a focus on Retrieval-Augmented Generation (RAG), document intelligence, knowledge bases, and AI SaaS products.
I can build systems that ingest your PDFs, documents, websites, databases, or APIs and turn them into grounded AI experiences with vector search, embeddings, source citations, and reliable retrieval.
What I can build:
- RAG chatbots & knowledge-base assistants
- Document Q&A and enterprise search
- AI SaaS and custom AI web applications
- Vector database and semantic search systems
- AI features for existing applications
- Secure APIs, authentication, dashboards, and integrations
Tech I work with:
Next.js, React, TypeScript, Python, FastAPI, PostgreSQL, Supabase, pgvector, Redis, Celery, Gemini, OpenAI, Claude, and modern AI APIs.
My focus is on clean architecture, scalable backend systems, practical AI integration, and clear source-grounded responses rather than raw LLM output.
Please message me before ordering so I can review your data sources, application scope, integrations, and deployment requirements.
Get to know Talal N.
Talal N.
Penetration Testing, Application Security, Full Stack Web Development
- FromPakistan
- Member sinceAug 2026
- Avg. response time1 hour
Languages
Urdu, English
Cybersecurity and full-stack developer focused on penetration testing, application security (AppSec), vulnerability assessment, DevSecOps, GRC, and secure web development. Hands-on with OWASP Top 10, Burp Suite, Nmap, Nessus, GitHub Actions, Docker, Python, Next.js, React, APIs, and security automation. I also work with GRC, including risk assessments, risk registers, security controls, compliance documentation, audit support, and ISO 27001-aligned processes. Clear reporting, practical solutions, and actionable recommendations.
FAQ
What kind of RAG AI applications can you build?
I can build document Q&A systems, knowledge-base assistants, internal search tools, customer-support AI, enterprise search, AI SaaS products, and custom RAG-powered web applications.
What data sources can the RAG system use?
Depending on the project, I can work with PDFs, documents, websites, PostgreSQL/Supabase databases, APIs, and other structured or unstructured data sources. Please message me first for custom connectors.
Do you only build chatbots?
No. I build full-stack AI applications. RAG chat interfaces are one use case, but I can also build dashboards, document intelligence tools, semantic search, APIs, knowledge systems, and AI features for existing products.
Can you integrate RAG or AI into my existing application?
Yes. I can integrate AI, vector search, document retrieval, or RAG functionality into an existing web application, provided the current architecture and codebase are compatible.
Which AI models and technologies can you work with?
I can work with providers such as OpenAI, Gemini, and Claude, along with Python, FastAPI, Next.js, TypeScript, PostgreSQL, Supabase, pgvector, Redis, Celery, and other tools depending on the project requirements.
How do you reduce hallucinations and inaccurate AI answers?
I use retrieval-based grounding, similarity filtering, carefully structured prompts, appropriate generation settings, and source citations where applicable. RAG can significantly reduce unsupported answers, but no LLM system can guarantee zero hallucinations.
Will I receive the source code?
Yes, source code is included when selected in your package. I can also provide setup instructions and technical documentation based on the agreed project scope.
Can you deploy the application for me?
Yes. I can help deploy the application to suitable cloud or hosting infrastructure. Hosting, database, and AI API costs are normally paid directly by the client through their own accounts.
Can you use Supabase for authentication, storage, PostgreSQL, or pgvector?
Yes. Supabase can be used for PostgreSQL, authentication, storage, and pgvector-based retrieval when it is a good fit for the application architecture.
Should I contact you before ordering?
Yes, please message me first. RAG projects can vary significantly based on data volume, integrations, authentication, infrastructure, and application complexity, so I prefer to confirm the scope before development begins.
