You will get a production-ready Prompt System with guardrails & QA
Project details
I build production-ready prompt systems that generate consistent, structured, and reliable outputs — not random “good prompts.”
You will receive a complete Prompt System Package designed for real business use:
• System prompt architecture + role instructions
• Guardrails to reduce hallucinations and enforce compliance
• Output format schema (JSON / Markdown / structured templates)
• Few-shot examples to stabilize performance
• Prompt iteration + refinement for edge cases
• Clear documentation so your team can reuse and scale it
This service is ideal if you need ChatGPT (or any LLM) to behave like a predictable tool for workflows such as customer support, content production, internal automation, sales messaging, research summarization, or structured reporting.
My approach is engineering-based: I test prompts like software, optimize for failure modes, and deliver documentation that makes the system usable long-term.
If you want prompt results that are consistent, scalable, and ready for production workflows, this project is built for that.
You will receive a complete Prompt System Package designed for real business use:
• System prompt architecture + role instructions
• Guardrails to reduce hallucinations and enforce compliance
• Output format schema (JSON / Markdown / structured templates)
• Few-shot examples to stabilize performance
• Prompt iteration + refinement for edge cases
• Clear documentation so your team can reuse and scale it
This service is ideal if you need ChatGPT (or any LLM) to behave like a predictable tool for workflows such as customer support, content production, internal automation, sales messaging, research summarization, or structured reporting.
My approach is engineering-based: I test prompts like software, optimize for failure modes, and deliver documentation that makes the system usable long-term.
If you want prompt results that are consistent, scalable, and ready for production workflows, this project is built for that.
AI Algorithms
Autoencoder, Feedforward Neural Network, Generative Adversarial Network, Large Language Model, Linear Discriminant Analysis, Multimodal Large Language Model, Recurrent Neural Network, Regression Analysis, Transformer Model, Variational AutoencoderAI Applications
AI Chatbot, AI Content Creation, AI Text-to-Image, AI-Enhanced Classification, AI-Generated Art, AI-Generated Code, AI-Generated Video, Conversational AI, Image Upscaling, Natural Language Generation, Natural Language Understanding, Synthetic Data GenerationAI Development Language
PythonAI Tools
Adobe Firefly, Azure OpenAI, Bing AI, Copy.ai, GitHub Copilot, Gradio, Hugging Face, Jasper AI, Microsoft 365 Copilot, StreamlitAI Models
BERT, BLOOM, ChatGPT, DALL-E, GPT-3, GPT-4, GPT-J, LLaMA, Midjourney AI, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$49
|
Standard
$99
|
Advanced
$199
|
|---|---|---|---|
| Delivery Time | 3 days | 3 days | 5 days |
Number of Revisions | 2 | 3 | 4 |
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.
Fast Delivery
+$20 - $60
Additional Revision
+$20
Prompt QA Test Suite
(+ 2 Days)
+$50
Few-Shot Examples Pack
(+ 1 Day)
+$40Frequently asked questions
About Ela
Prompt Engineer | LLM Prompt Systems, Guardrails & Evaluation
Istanbul, Turkey - 7:44 am local time
Not “cool demos”—but structured prompts designed for real business workflows: customer support, content pipelines, research assistants, internal tools, and retrieval-based Q&A.
My focus is reliability engineering for LLM outputs:
Reducing hallucinations
Improving formatting consistency
Enforcing constraints
Designing prompts that survive edge cases
If you need prompts that work in production (not only in a chat window), you’re in the right place.
Steps for completing your project
After purchasing the project, send requirements so Ela can start the project.
Delivery time starts when Ela receives requirements from you.
Ela works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Analysis & Prompt System Blueprint
I review your use case, constraints, and examples, then define the prompt architecture, output schema, and failure-mode risks before writing the system.
System Prompt + Guardrails Development
I design a production-grade system prompt with strict instructions, formatting rules, tone controls, and hallucination prevention mechanisms.