You will get LLM & RAG Architecture Design Consultation (Production-Focused, 60–90 mins)
Project details
Organizations exploring Large Language Model (LLM) initiatives often move too quickly into development without a structured architecture or cost framework. This session is designed to provide a clear, production-oriented system blueprint before implementation begins.
You will receive a structured evaluation of your use case, technical constraints, and scalability requirements, followed by a practical architecture outline covering model abstraction, retrieval design (RAG), orchestration logic, deployment topology, monitoring strategy, and cost modeling.
This is not a generic AI discussion. The outcome is a decision-grade architecture plan that reduces implementation risk, avoids unnecessary vendor lock-in, and establishes predictable cost control.
Suitable for:
• CTOs and technical founders
• Product teams evaluating LLM adoption
• Enterprises transitioning from prototype to production
• Startups preparing investor-ready technical architecture
Deliverables vary by tier and may include a written blueprint document and implementation roadmap. Timeline begins after required materials are received and session availability is confirmed.
You will receive a structured evaluation of your use case, technical constraints, and scalability requirements, followed by a practical architecture outline covering model abstraction, retrieval design (RAG), orchestration logic, deployment topology, monitoring strategy, and cost modeling.
This is not a generic AI discussion. The outcome is a decision-grade architecture plan that reduces implementation risk, avoids unnecessary vendor lock-in, and establishes predictable cost control.
Suitable for:
• CTOs and technical founders
• Product teams evaluating LLM adoption
• Enterprises transitioning from prototype to production
• Startups preparing investor-ready technical architecture
Deliverables vary by tier and may include a written blueprint document and implementation roadmap. Timeline begins after required materials are received and session availability is confirmed.
AI Algorithms
Convolutional Neural Network, Large Language Model, Long Short-Term Memory Network, Multimodal Large Language Model, Recurrent Neural Network, Regression Analysis, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI-Enhanced Classification, AI-Generated Code, AIOps, Anomaly Detection, Conversational AI, Image Processing, Natural Language Generation, Natural Language Understanding, Speech Synthesis, Time Series ForecastingAI Development Language
PythonAI Tools
Azure OpenAI, Hugging Face, NVIDIA AI Platform, PyTorch, Streamlit, TensorFlowAI Models
BERT, BLOOM, ChatGPT, GPT-3, GPT-4, GPT-Neo, LLaMA, Naive Bayes Classifier, OpenAI Codex, WhisperWhat's included
| Service Tiers |
Starter
$199
|
Standard
$349
|
Advanced
$590
|
|---|---|---|---|
| Delivery Time | 4 days | 6 days | 8 days |
Number of Revisions | 1 | 2 | 3 |
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.
30-min Follow-up Session
+$129Frequently asked questions
About Ling
Production AI Systems | LLM & RAG Architecture | PhD
Singapore, Singapore - 7:06 am local time
I design and implement production-ready machine learning and LLM systems that move beyond experimentation into stable, scalable infrastructure. My work focuses on delivering systems that operate reliably in real workflows — not demos or prototypes.
With 20+ years across academia and industry, including leadership roles in large-scale e-commerce platforms, I have built predictive intelligence and AI infrastructure serving multi-million user environments. My experience spans architecture design, system optimization, and production deployment.
Selected impact:
• Led ML initiatives driving 8–16% revenue uplift in large-scale commerce systems
• Built predictive intelligence pipelines operating at multi-million user scale
• Winner of 10+ international ML competitions
• 80+ peer-reviewed publications in top-tier venues
What I help clients build:
• Production-ready LLM and RAG systems
• AI knowledge assistants and internal document Q&A platforms
• Retrieval pipelines with vector databases and optimized search
• Scalable ML infrastructure aligned with business objectives
• Technical architecture review and ML due diligence
I do not sell isolated models or generic AI prototypes.
I design structured AI systems that are deployable, maintainable, and aligned with measurable outcomes.
If you are building an AI-driven product, integrating LLM into workflows, or transitioning from prototype to production — I can help structure the architecture and execution roadmap.
Steps for completing your project
After purchasing the project, send requirements so Ling can start the project.
Delivery time starts when Ling receives requirements from you.
Ling works on your project following the steps below.
Revisions may occur after the delivery date.
Initial Review of Requirements
I review your submitted objectives, constraints, and technology context prior to the session.
Structured Strategy Session (60–90 mins)
We evaluate use cases, architecture options, risk trade-offs, and scalability considerations.