You will get a private RAG AI chatbot connected to your knowledge base
Rising Talent
Rising Talent
Project details
Give your team instant access to accurate information with a private AI chatbot built specifically for your business. Instead of relying on public AI models with outdated or incomplete knowledge, your chatbot will securely search your own documents and generate reliable answers using Retrieval-Augmented Generation (RAG).
I build production-ready RAG systems that connect to PDFs, Word documents, websites, Notion, Confluence, SharePoint, Google Drive, cloud storage, databases, and internal business systems. The chatbot can answer questions, summarize documents, compare information, extract data, and help employees find exactly what they need in seconds.
Every solution is designed with security, scalability, and accuracy in mind. I implement document indexing, vector databases, semantic search, citation support, authentication, user permissions, conversation history, and modern web interfaces. Whether you need an internal company assistant, customer knowledge portal, support documentation chatbot, or enterprise AI search platform, you'll receive a fully customized solution built around your business.
I build production-ready RAG systems that connect to PDFs, Word documents, websites, Notion, Confluence, SharePoint, Google Drive, cloud storage, databases, and internal business systems. The chatbot can answer questions, summarize documents, compare information, extract data, and help employees find exactly what they need in seconds.
Every solution is designed with security, scalability, and accuracy in mind. I implement document indexing, vector databases, semantic search, citation support, authentication, user permissions, conversation history, and modern web interfaces. Whether you need an internal company assistant, customer knowledge portal, support documentation chatbot, or enterprise AI search platform, you'll receive a fully customized solution built around your business.
AI Algorithms
AdaBoost, Convolutional Neural Network, Feedforward Neural Network, Large Language Model, Linear Discriminant Analysis, Multilayer Perceptron, Multimodal Large Language Model, Recurrent Neural Network, Self-Organizing Map, Variational AutoencoderAI Applications
AI Chatbot, AI Mobile App Development, AI Text-to-Image, AI-Enhanced Classification, AI-Enhanced Medical Imaging, AI-Generated Art, AI-Generated Music, Anomaly Detection, Conversational AI, Facial Recognition, Image Recognition, Text RecognitionAI Development Language
PythonAI Tools
Adobe Firefly, Azure OpenAI, Copy.ai, GitHub Copilot, Gradio, Jasper AI, Microsoft 365 Copilot, Microsoft CNTK, PyTorch, StreamlitAI Models
AlphaCode, BERT, BLOOM, ChatGPT, Dolly, GPT-3, GPT-J, GPT-Neo, Jurassic-2, Naive Bayes Classifier, OpenAI Codex, Stable DiffusionWhat's included
| Service Tiers |
Starter
$900
|
Standard
$2,100
|
Advanced
$4,200
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 2 | 3 | 5 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | - | - |
Detailed Code Comments | |||
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | - |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | |||
Model Tuning | - | - | - |
Natural Language Processing | |||
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | - | - | - |
Source Code | - | - | - |
About Vishal
AI Agent Engineer - Custom LLM Apps, MCP, Connectors & Agentic Systems
London, United Kingdom - 11:52 am local time
I build custom AI agent systems for teams that need AI to do real work across tools, data, APIs, documents, and business operations.
The offer is simple:
Bring me one expensive, repetitive operating process. I will help turn it into a working AI agent or LLM-powered application your team can actually use.
This is not a generic chatbot, prompt wrapper, or no-code automation setup. I build custom agentic software around your real systems, business rules, permissions, data, and users.
𝗚𝗼𝗼𝗱 𝗳𝗶𝗿𝘀𝘁 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀
- Strategic sourcing
- Account intelligence
- Executive reporting
- RevOps data quality
- Customer escalation routing
- Compliance or document review
- Vendor due diligence
- Internal knowledge systems
- Agent-ready product integrations with MCP, plugins, and connectors
𝗪𝗵𝗮𝘁 𝗜 𝗯𝘂𝗶𝗹𝗱
- Custom AI agents and LLM-powered internal apps
- RAG and knowledge systems over private documents, databases, websites, and business data
- MCP servers, plugins, connectors, custom agent skills, and agent-ready APIs
- Browser/API agents that inspect pages, prepare outputs, and execute supervised tasks
- AI dashboards and operating tools connected to real business data
- Human-in-the-loop systems where accuracy, approval, and auditability matter
- Multi-tool agents across CRMs, spreadsheets, SaaS tools, databases, portals, and internal systems
𝗠𝘆 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵
Most AI projects fail because they start too broad.
I keep the first build narrow:
- One process
- One user group
- One measurable outcome
- One working system your team can test
That gives you a practical first version before you commit to a larger AI build.
𝗪𝗵𝗮𝘁 𝗜 𝗱𝗲𝗹𝗶𝘃𝗲𝗿
- Process map covering inputs, decisions, tools, data, actions, approvals, and failure cases
- Working LLM-powered agent or application connected to your real systems
- Tool layer: APIs, connectors, MCP servers, plugins, browser execution, or custom skills
- Reliability layer: permissions, memory/RAG, retries, logs, human approval, and handoff
- Product layer: UI, dashboard, backend, deployment, and documentation
𝗪𝗵𝘆 𝗰𝗹𝗶𝗲𝗻𝘁𝘀 𝗵𝗶𝗿𝗲 𝗺𝗲
I reduce broad AI ideas into focused systems that can ship.
I build the operational parts that make AI agents usable: authentication, data access, state, tool calls, approvals, retries, logs, UI, deployment, and integrations.
I work across the full stack: LLM orchestration, backend APIs, databases, browser automation, frontend dashboards, authentication, deployment, and agent tooling.
𝗚𝗼𝗼𝗱 𝗳𝗶𝘁
You may be a good fit if:
- Your team wastes hours every week on a repeated operating process
- You need an AI agent that can use tools, not just answer questions
- You have an AI prototype that is interesting but not usable yet
- Your product needs an MCP server, plugin, connector, or agent skill
- You need reliable answers and next actions from documents, databases, websites, or internal systems
𝗡𝗼𝘁 𝗮 𝗴𝗼𝗼𝗱 𝗳𝗶𝘁
I am probably not the right fit for generic prompt-only chatbots, one-off scripts, or projects where accuracy, permissions, data access, and reliability do not matter.
If you can point to one painful operating process, I can help turn it into a working AI agent system.
Steps for completing your project
After purchasing the project, send requirements so Vishal can start the project.
Delivery time starts when Vishal receives requirements from you.
Vishal works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1 — Analyze Knowledge Sources
Review your documents, databases, and knowledge repositories to determine the best RAG architecture.
Step 2 — Build Knowledge Pipeline
Prepare documents, generate embeddings, configure vector database, and optimize retrieval quality.