You will get RAG AI chatbot on your business data for support, sales, and internal FAQs
Top Rated
Project details
I will build a custom AI chatbot that answers questions using your documents, not the public internet. Your team will be able to upload content, and the bot will search this data in real time to give accurate, source-grounded answers.
For each project, I start with a short discovery to clarify your use case and the data sources. You will get a working chatbot, a walkthrough call, and simple instructions on how to add or update content in the future.
Best use cases for this chatbot:
1) Customer support: Answer product, policy, and troubleshooting questions using your docs, and past tickets, reducing support load and response times.
2) Sales & lead qualification: Let prospects ask questions about pricing, features, and comparisons using your sales collateral, then pass them to your team.
3) Internal knowledge base for team: Give your staff a single chat interface over SOPs, playbooks, and project docs so they stop digging through folders and old messages.
4) Document-heavy workflows: Search contracts, reports, FAQs, or manuals and return summarized answers with references to the original pages.
Ready to get started?
For each project, I start with a short discovery to clarify your use case and the data sources. You will get a working chatbot, a walkthrough call, and simple instructions on how to add or update content in the future.
Best use cases for this chatbot:
1) Customer support: Answer product, policy, and troubleshooting questions using your docs, and past tickets, reducing support load and response times.
2) Sales & lead qualification: Let prospects ask questions about pricing, features, and comparisons using your sales collateral, then pass them to your team.
3) Internal knowledge base for team: Give your staff a single chat interface over SOPs, playbooks, and project docs so they stop digging through folders and old messages.
4) Document-heavy workflows: Search contracts, reports, FAQs, or manuals and return summarized answers with references to the original pages.
Ready to get started?
Chatbot Type
Customer Service Chatbot, Productivity ChatbotDevelopment Technology
Azure Bot Service, ChatGPT, GPT-3Messaging Platform
Email, Website, WhatsAppWhat's included
| Service Tiers |
Starter
$400
|
Standard
$800
|
Advanced
$1,500
|
|---|---|---|---|
| Delivery Time | 7 days | 11 days | 21 days |
Number of Revisions | 1 | 2 | 3 |
Number of Conversation Steps | 2 | 3 | 7 |
Number of Messaging Platforms | 1 | 2 | 6 |
Action Plan | - | - | |
API Integration | - | - | |
Bug Fixes | |||
Chatbot Flow Design | |||
Conversation Script | - | - |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$200 - $600
Additional Revision
+$200
Additional Conversation Step
(+ 2 Days)
+$300
Additional Messaging Platform
(+ 2 Days)
+$300
Action Plan
(+ 1 Day)
+$100
API Integration
(+ 3 Days)
+$400
Conversation Script
(+ 1 Day)
+$250Frequently asked questions
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Wonderful experience. Successful project.
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Vivek did an outstanding job implementing custom code that my team struggled with. He consistently delivered elegant solutions for complex website challenges, handling integrations with ease and keeping communication clear throughout. His work made web development seamless. Highly recommended.
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Feb 4, 2026
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About vivek
AI Engineer | RAG Chatbots, n8n Automation & LLM Apps in Production
100%
Job Success
Jaipur, India - 1:10 pm local time
16+ years scaling SaaS platforms. $400K+ earned on Upwork. Expert-Vetted Top 1% | 100% Job Success.
I’m Vivek Sharma, founder of Provis Technologies. I help SaaS companies and operations teams build AI automation systems using GPT, RAG chatbots, and n8n workflows to reduce manual work and improve efficiency. If you are looking for: an AI chatbot developer, a RAG chatbot for your business data, an n8n automation expert, a GPT-based workflow automation AI support chatbot, or an internal AI assistant
→ This is exactly what I specialize in. Most businesses don’t need more AI demos. They need AI systems that work inside real operations, reducing workload, improving response time, and automating repetitive processes.
Core Solutions:
AI Chatbot & RAG Systems
→ RAG chatbot built on your internal data
→ GPT chatbot for customer support and sales
→ AI knowledge base assistant
→ Document search and retrieval systems
→ AI chatbot with vector database
n8n Workflow Automation
→ n8n automation setup and optimization
→ Workflow automation using APIs
→ CRM, Slack, email integrations
→ Lead routing and pipeline automation
→ Business process automation
AI Automation Systems
→ AI workflow automation using GPT
→ AI agents for operations and support
→ AI lead qualification systems
→ Internal AI copilots
→ AI automation for SaaS platforms
SaaS MVP Development
→ AI-powered SaaS MVP
→ Multi-tenant SaaS architecture
→ Backend systems and APIs
→ Scalable cloud-ready applications
Results:
✔ Built RAG chatbot, improving document search by 80%
✔ Developed an AI chatbot, reducing support workload by 60%
✔ Created n8n automation workflows saving 20+ hours/week
✔ Reduced operational costs by 25% for the B2B platform
✔ Delivered AI-powered SaaS MVP in under 6 weeks
Tech Stack:
AI / LLMs: GPT, OpenAI API, Claude, RAG, vector databases, AI agents
Automation: n8n, API integration, workflow automation
Backend: Node.js, Python, FastAPI
Frontend: React, Next.js
Cloud: AWS, Docker, CI/CD
Why Clients Hire Me
✔ Focus on real business outcomes, not AI experiments
✔ Strong SaaS and automation architecture experience
✔ Scalable, production-ready systems
✔ Fast execution with clear communication
✔ Long-term collaboration mindset
Let’s Talk, If you need RAG chatbot, AI chatbot, n8n automation, AI workflow system, SaaS MVP with AI
Send your workflow or problem. I’ll map the fastest way to build and deploy it.
Steps for completing your project
After purchasing the project, send requirements so vivek can start the project.
Delivery time starts when vivek receives requirements from you.
vivek works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery & data audit
Clarify use case, review sample documents, confirm scope and stack.
Data ingestion & indexing
Clean and chunk documents, set up vector database, and connect to LLM.