You will get Build a Custom AI Tool (Summarizer, Generator, Content Automation)
Project details
Launch your AI-powered micro-tool fast! Get a ready-to-use MVP for summarization, rewriting, or content generation. Perfect for startups or businesses testing AI features without full-scale investment. Includes smart LLM pipeline, prompt-engineered logic, sleek UI (Streamlit/React), refined outputs, and seamless deployment. Choose from Basic, Standard, or Premium packages for increasing functionality, memory, and business personalization.
💲 Basic — $300
Included
• One small AI tool (summary, rewrite, small generator)
• Basic UI (Gradio)
• One prompt-engineered pipeline
• Two output variants
• API key setup
• Deployment
💲 Standard — $600
Included
• Full workflow
• 2–3 functions (summary + enrichment + rewrite, etc.)
• Better UI (Streamlit / React)
• Prompt chain
• Quality control + fallback prompts
• One integration endpoint
💲 Premium — $1200
Included
• MVP with production-ready structure
• Multi-step pipeline
• Context memory
• Business-level personalization
• Deployment
• Auth
• Logging + error handling
• Documentation
💲 Basic — $300
Included
• One small AI tool (summary, rewrite, small generator)
• Basic UI (Gradio)
• One prompt-engineered pipeline
• Two output variants
• API key setup
• Deployment
💲 Standard — $600
Included
• Full workflow
• 2–3 functions (summary + enrichment + rewrite, etc.)
• Better UI (Streamlit / React)
• Prompt chain
• Quality control + fallback prompts
• One integration endpoint
💲 Premium — $1200
Included
• MVP with production-ready structure
• Multi-step pipeline
• Context memory
• Business-level personalization
• Deployment
• Auth
• Logging + error handling
• Documentation
Machine Learning Tools
Azure Machine Learning, ChatGPT, GitHub Copilot, Google AutoML, Google Sheets, GPT-3, Keras, MATLAB, Microsoft Excel, Microsoft Power BI, MLflow, NumPy, pandas, Python, PyTorch, SQL, TensorFlowWhat's included
| Service Tiers |
Starter
$300
|
Standard
$600
|
Advanced
$1,200
|
|---|---|---|---|
| Delivery Time | 5 days | 10 days | 15 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 1 | 3 |
Number of Scenarios | 1 | 3 | 5 |
Model Validation/Testing | - | - | |
Model Documentation | |||
Data Source Connectivity | |||
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$150 - $600
Additional Model Variation
(+ 1 Day)
+$200
Additional Scenario
(+ 1 Day)
+$200
Additional Graph/Chart
(+ 1 Day)
+$200
Model Validation/Testing
(+ 1 Day)
+$200About Kyrylenko
AI Dev Team Lead
Kyiv, Ukraine - 9:24 pm local time
Experienced Project Manager with a specialization in artificial intelligence projects. I am able to combine a deep understanding of AI technologies with a clear organization of processes to deliver business value in a timely and efficient manner.
Key skills:
Project management: Agile (Scrum, Kanban), Waterfall, hybrid approaches
AI/ML technologies: NLP, computer vision, generative models (GPT, BERT, Diffusion)
Tools: Jira, Asana, Trello, Git, MLflow, Figma, Intercom FIN AI automation.
Communication: meeting facilitation, presentations for stakeholders, writing technical and business documents
Analytics: setting success metrics (OKR, KPI), data analysis, A/B testing
Risk management: risk identification, reserve planning, change control
Experience.
Implementation of chatbots based on GPT-4 for customer support (reduction of response time by 40%)
Coordinating the development of computer vision systems for automating quality control in production
Developing roadmaps, managing a team of 4-7 engineers and analysts
Supporting Agile processes in the Data Science team
Preparation of technical specifications for machine learning models
Monitoring model performance, preparing reports for C-leve
Steps for completing your project
After purchasing the project, send requirements so Kyrylenko can start the project.
Delivery time starts when Kyrylenko receives requirements from you.
Kyrylenko works on your project following the steps below.
Revisions may occur after the delivery date.
Requirements & Use Case Analysis
Clarifying the goal, function, and expected AI behavior.
LLM Pipeline Setup
Building a prompt-engineered pipeline for the selected AI function.