You will get an AI MVP prototype rescued and planned for launch
Top Rated
Project details
I will turn your AI product idea or rough prototype into a realistic build path.
This is for founders and small teams who have an AI app idea, a rough low-code or agent-built prototype, a half-working demo, or a repo that needs product-engineering judgment before more money is spent. The goal is to cut scope, identify risks, define acceptance criteria, and either rescue the prototype or build the first useful sprint.
The output is practical: architecture, data flow, API/model cost risks, UX constraints, acceptance criteria, delivery plan and, on implementation tiers, working prototype improvements.
Good fit:
• LLM API apps and AI SaaS MVPs
• internal copilots, document AI, workflow tools and automation apps
• prototype rescue from AI app builders, coding agents or low-code tools
• early demos that need reliability, product scope or deployment cleanup
Not a fit:
• guaranteed fundraising or guaranteed user growth
• legal, medical or financial advice as the final product claim
• production claims without validation and acceptance criteria
I can include an implementation note, risk table and acceptance checklist for the next sprint.
This is for founders and small teams who have an AI app idea, a rough low-code or agent-built prototype, a half-working demo, or a repo that needs product-engineering judgment before more money is spent. The goal is to cut scope, identify risks, define acceptance criteria, and either rescue the prototype or build the first useful sprint.
The output is practical: architecture, data flow, API/model cost risks, UX constraints, acceptance criteria, delivery plan and, on implementation tiers, working prototype improvements.
Good fit:
• LLM API apps and AI SaaS MVPs
• internal copilots, document AI, workflow tools and automation apps
• prototype rescue from AI app builders, coding agents or low-code tools
• early demos that need reliability, product scope or deployment cleanup
Not a fit:
• guaranteed fundraising or guaranteed user growth
• legal, medical or financial advice as the final product claim
• production claims without validation and acceptance criteria
I can include an implementation note, risk table and acceptance checklist for the next sprint.
AI Algorithms
Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI-Generated Code, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Hugging Face, PyTorch, Replit, StreamlitAI Models
ChatGPT, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$350
|
Standard
$1,250
|
Advanced
$2,500
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 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.
Extra integration/API
(+ 3 Days)
+$300
Deployment support
(+ 3 Days)
+$400
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About Zakhar
Senior Computer Vision & OCR Engineer | Edge AI, Production AI
100%
Job Success
Yerevan, Armenia - 12:32 pm local time
My strongest fit is a project with real data, a broken or uncertain pipeline, and measurable acceptance targets: accuracy, false positives, latency, edge-device constraints, cost, security, or launch readiness.
Core work:
- Computer vision / OCR: detection, segmentation, tracking, image analysis, OCR extraction, validation, reviewer workflows
- Edge AI: ONNX/TensorRT conversion, model optimization, quantization-aware deployment, mobile/on-device inference
- AI backend: OpenAI API, RAG, VLMs, source traces, confidence checks, FastAPI, PostgreSQL
- Production delivery: tests, logging, monitoring, cloud deployment, handoff docs
I am a good fit when AI output must be accurate, fast enough for production, reviewable, logged, and reliable enough for real business use.
Steps for completing your project
After purchasing the project, send requirements so Zakhar can start the project.
Delivery time starts when Zakhar receives requirements from you.
Zakhar works on your project following the steps below.
Revisions may occur after the delivery date.
Scope, risks and MVP plan
I review requirements, current prototype or repo, define the smallest useful workflow, risks, acceptance criteria and next implementation actions.