You will get Secure RAG Knowledge System Deployment
Project details
Most teams experimenting with AI encounter the same problem: the system generates confident responses, but no one can verify where the information came from.
This engagement delivers a structured, secure Retrieval-Augmented Generation (RAG) knowledge system designed for internal use. The system retrieves answers strictly from your indexed documents, enforces citation-backed responses, and operates within defined boundaries to reduce hallucination risk.
This is not a generic chatbot. It is a controlled internal knowledge layer built for professional teams managing manuals, policies, technical documentation, or operational records.
The pilot includes document ingestion, vector-based retrieval, bounded generation logic, deployment in your preferred environment, and validation testing. The objective is to deliver a governed proof-of-value system that is auditable, stable, and scalable without committing to a full platform build.
If you need internal AI that is structured, traceable, and aligned with operational governance, this pilot provides a disciplined starting point.
This engagement delivers a structured, secure Retrieval-Augmented Generation (RAG) knowledge system designed for internal use. The system retrieves answers strictly from your indexed documents, enforces citation-backed responses, and operates within defined boundaries to reduce hallucination risk.
This is not a generic chatbot. It is a controlled internal knowledge layer built for professional teams managing manuals, policies, technical documentation, or operational records.
The pilot includes document ingestion, vector-based retrieval, bounded generation logic, deployment in your preferred environment, and validation testing. The objective is to deliver a governed proof-of-value system that is auditable, stable, and scalable without committing to a full platform build.
If you need internal AI that is structured, traceable, and aligned with operational governance, this pilot provides a disciplined starting point.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI-Enhanced Classification, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Azure OpenAI, Gradio, Hugging Face, PyTorch, StreamlitAI Models
ChatGPT, GPT-4, LLaMA, WhisperWhat's included
| Service Tiers |
Starter
$2,500
|
Standard
$3,500
|
Advanced
$4,500
|
|---|---|---|---|
| Delivery Time | 14 days | 21 days | 28 days |
Number of Revisions | 1 | 2 | 2 |
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 |
Optional add-ons
You can add these on the next page.
Accelerated Delivery
+$625
Extended Corpus Expansion
+$950
Deployment Hardening & Access Controls
+$1,200Frequently asked questions
About Gareth
AI & Systems Risk Architect | Architecture Reviews
Grovetown, United States - 11:16 am local time
My work focuses on architecture coherence, identity boundaries, AI integration risk, and structural failure modes. I do not implement tools or manage cloud environments. Instead, I provide independent written reviews that surface hidden assumptions, single points of failure, and governance gaps before they become expensive problems.
I specialize in:
• AI workflow risk assessment
• Identity and boundary evaluation
• Failure-mode analysis
• Architecture review prior to scaling
• Vendor proposal and security claim analysis
I work best with teams integrating AI or cloud-based systems who want structural clarity before committing to implementation.
Engagements result in structured written assessments with prioritized findings and containment recommendations not generic checklists, and not tool configuration.
If you’re building something and want to understand what breaks first and why that’s where I come in.
Steps for completing your project
After purchasing the project, send requirements so Gareth can start the project.
Delivery time starts when Gareth receives requirements from you.
Gareth works on your project following the steps below.
Revisions may occur after the delivery date.
Corpus & Scope Alignment
We review document size, structure, and deployment environment to confirm pilot scope and architecture approach.
Ingestion & Indexing Setup
Documents are processed, structured, and indexed into a retrieval system with controlled metadata tagging.