You will get AI workflow discovery and a testable working prototype
Project details
Not every workflow needs an “AI agent,” and a demo is not the same as a production system.
I will map one real business workflow, identify where AI is useful, review data, APIs, permissions and failure risks, and build a bounded prototype of the core path.
Depending on the package, the prototype may include document-grounded answers, structured output, one tool/API call, human approval and basic audit events.
You will receive a workflow map, feasibility and risk findings, a testable prototype, recommended architecture, and a practical implementation plan.
This is a discovery and validation service. It does not include production deployment, enterprise SSO, unrestricted system access, bulk data migration, security certification or unlimited revisions.
I will map one real business workflow, identify where AI is useful, review data, APIs, permissions and failure risks, and build a bounded prototype of the core path.
Depending on the package, the prototype may include document-grounded answers, structured output, one tool/API call, human approval and basic audit events.
You will receive a workflow map, feasibility and risk findings, a testable prototype, recommended architecture, and a practical implementation plan.
This is a discovery and validation service. It does not include production deployment, enterprise SSO, unrestricted system access, bulk data migration, security certification or unlimited revisions.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Models
ChatGPT, GPT-4What's included
| Service Tiers |
Starter
$295
|
Standard
$695
|
Advanced
$1,290
|
|---|---|---|---|
| Delivery Time | 3 days | 5 days | 7 days |
Number of Revisions | 1 | 1 | 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 | - |
Frequently asked questions
About Lielie
AI App & Systems Integration Engineer | APIs, Automation, DevOps
Changzhou, China - 7:58 pm local time
If you need more than a chatbot demo, I can turn a repetitive business process into a working web application, automation, AI agent, or internal tool. I handle the full delivery process—from requirements and architecture to APIs, databases, deployment, testing, and ongoing support.
With 15+ years of software delivery experience, I have built and maintained enterprise and public-sector systems that require reliability, security, and long-term operation.
I can help you with:
- AI agents and workflow automation
- AI integration for existing web applications
- Internal tools, dashboards, and admin portals
- API, webhook, database, and third-party integrations
- Document processing, reporting, search, and knowledge systems
- Legacy system modernization, debugging, and on-premises deployment
My approach is practical: define the workflow and acceptance criteria, build a testable milestone, verify edge cases, and then make the system stable enough for daily use.
Send me your current workflow, files, or system requirements. I can help you identify the simplest reliable solution before development begins.
Steps for completing your project
After purchasing the project, send requirements so Lielie can start the project.
Delivery time starts when Lielie receives requirements from you.
Lielie works on your project following the steps below.
Revisions may occur after the delivery date.
Workflow intake and scope confirmation
Review requirements, samples, users, goals, constraints and acceptance examples; confirm the bounded workflow for the selected package.
Process, data, API and risk analysis
Map the current process and system boundaries, then assess data quality, integrations, permissions, failure modes and practical AI fit.