You will get reduced LLM costs and optimized AI automations

Project details
I review AI automations and find where you overpay for LLM usage.
This project is for teams and founders who already use AI in workflows, bots, or internal automations but want to reduce API costs, improve model selection, and get a better balance between price, speed, and output quality. I analyze the current setup, identify unnecessary spending, and provide practical recommendations to optimize your AI workflow.
Best fit for LLM cost reduction, model selection, prompt optimization, routing strategy, and AI workflow efficiency.
This project is for teams and founders who already use AI in workflows, bots, or internal automations but want to reduce API costs, improve model selection, and get a better balance between price, speed, and output quality. I analyze the current setup, identify unnecessary spending, and provide practical recommendations to optimize your AI workflow.
Best fit for LLM cost reduction, model selection, prompt optimization, routing strategy, and AI workflow efficiency.
AI Algorithms
Large Language ModelAI Applications
AI Content Creation, AI Text-to-SpeechAI Models
ChatGPTWhat's included
| Service Tiers |
Starter
$39
|
Standard
$79
|
Advanced
$149
|
|---|---|---|---|
| Delivery Time | 2 days | 3 days | 5 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.
Fast Delivery
+$25
Additional Revision
+$15
Implementation of recommendations
(+ 2 Days)
+$50Frequently asked questions
1 review
(1)
(0)
(0)
(0)
(0)
This project doesn't have any reviews.
VR
Vladimir R.
Mar 16, 2026
Lead Intake Process Automation Specialist
Fantastic experience! Vadym delivered exactly what was promised: a fully automated inquiry pipeline. We already started to experience its results: more free time for us and joy from seeing this automation is working for us. Will definitely be working with Vadym again in the future!
About Vadym
AI Automation Engineer | n8n Developer | Workflow Architect
Valencia, Spain - 8:59 pm local time
I help businesses design, fix, and optimize n8n workflows, AI automations, API integrations, and self-hosted automation systems. My work includes custom workflow development, debugging broken automations, reducing LLM costs, and deploying reliable production-ready setups with monitoring.
My background combines engineering, QA, and machine learning. I have 5+ years in banking tech and a PhD in Mathematics, which helps me approach automation as an engineer: clear logic, stability, testing, and measurable results.
What I do:
Custom n8n workflows and business automation
API, webhook, CRM, database, email, and messenger integrations
Debugging and fixing broken automations
LLM cost optimization and AI workflow improvement
Self-hosted n8n setup, deployment, monitoring, and support
I handle the full cycle from architecture to production:
Workflow design and implementation
Server setup and hardening
Docker, SSL, domains, and deployment
Monitoring, alerts, and error tracking
Testing and documentation before handoff
Recent work includes:
News automation system with 40 locales, hourly scheduling, and auto-publishing
Lead intake automation from web form to CRM to notification in under 30 seconds
RAG-powered Telegram assistants running in production
One person, full cycle: architecture → build → test → deploy → monitor → documentation.
Valencia, Spain (CET). Let’s talk.
Steps for completing your project
After purchasing the project, send requirements so Vadym can start the project.
Delivery time starts when Vadym receives requirements from you.
Vadym works on your project following the steps below.
Revisions may occur after the delivery date.
Review the current setup
I review the workflow, model usage, prompts, call structure, and current cost drivers.
Find optimization opportunities
I identify where you overpay, where simpler models can be used, and how to improve cost, speed, and output quality.