Sam Jin | AI Builder | AI Deploy Network

About Sam

AI full-stack developer delivering end-to-end LLM/RAG solutions, AI agent orchestration and desktop automation. Building AI Congress Online (multi-model cross-validation for reproducible data cleaning), sendguard (privacy-first process-level network control for Windows), LaneFlow-Free (lane detection) and armory-rightclick (OSINT workflow automation). Bilingual EN/Chinese, remote-first, open to freelance and contract work. GitHub: github.com/kinsin818

Professional profile

Location: Shenyang, China
Time zone: Asia/Shanghai
Work mode: Remote
Availability: Available for Contract Projects
AI experience: 1+ years
Languages: English, Mandarin Chinese
Working hours: 09:00–18:00 CST (UTC+8), Mon–Fri
Typical response: Within 24 hours
Preferred engagement: Small (individual or single team)
Travel: No travel
Available in: China

Proven on the network

Implementation records and publicly available work, where published.

4 AI Deployments delivered, including 4 publicly identified implementations available to inspect.

What Sam builds

Implementation domains listed on this profile. Evidence-supported items are identified separately below.

Specialisations

AI Agents

Intelligent Automation

Multimodal AI

Prompt & Context Engineering

RAG & Knowledge Retrieval

Builder-listed deployment types

AI Agent
AI Evaluation Framework
Computer Vision
Workflow Automation

AI Deployments

Real AI implementations demonstrated through evidence.

01 / AI DeploymentPublished record

SendGuard — Privacy-First Process-Level Network Control for Windows

An open-source Python tool that gives users process-level control over Windows network access, enforcing privacy by allowing or blocking applications from connecting at the process level.

Cybersecurity · Workflow Automation

View Deployment

02 / AI DeploymentPublished record

LaneFlow-Free — Real-Time Lane Detection for Driving Assistance

An open-source C# implementation of real-time lane detection for driving-assistance and computer-vision use cases, built to be lightweight and easy to integrate into .NET stacks.

Automotive · Computer Vision

View Deployment

03 / AI DeploymentPublished record

Armory Right-Click — OSINT Workflow Automation for Intelligence Gathering

An open-source Python desktop tool that automates OSINT (open-source intelligence) gathering workflows from the Windows right-click menu, turning repetitive multi-step research into single actions.

Cybersecurity · Workflow Automation

View Deployment

04 / AI DeploymentPublished record

AI Congress Online — Multi-Model Cross-Validation Platform for Reproducible Data Cleaning

A live public AI platform that runs multiple LLMs on the same data-cleaning task and cross-validates their outputs, making AI-assisted pipelines reproducible and audit-friendly.

Software & SaaS · AI Agent · AI Evaluation Framework · Workflow Automation

View Deployment

Implementation capabilities

Evidence-supported means linked to a published Deployment or Case Study; other capabilities are Builder declared.

Evidence-supported

AI Agent1 record
AI Evaluation Framework1 record
Computer Vision1 record
Workflow Automation3 records

Builder declared

AI Agents
Intelligent Automation
Multimodal AI
Prompt & Context Engineering
RAG & Knowledge Retrieval

Technology

Technologies listed by the Builder, distinguished by published evidence.

Evidence-supported

C#1 record
Python2 records

Builder declared

Go
Java

Industry experience

Published Deployments support the listed counts. Other industries are Builder declared.

Cybersecurity

2 published Deployments

Automotive

1 published Deployment

Software & SaaS

1 published Deployment

Cross-Industry / Horizontal

Builder declared

Trust & verification

A closer look at how this profile and its evidence are reviewed.

Community Member

Published evidence is reviewed against the AI Deploy Network Evidence Standard.

How verification works

Community

Verified Builder

Independently reviewed by AI Deploy Labs against the platform Evidence Standard.

How this is verifiedWhat the platform has established, and what remains builder-declared.

Identity and organisation: Identity checks confirm that the person presenting this profile controls the account and the professional identifiers attached to it, such as a LinkedIn profile. Organisation membership is confirmed by the organisation, not self-declared by the builder.
AI Deployments: An approved AI Deployment is an implementation record the builder submitted and the platform reviewed against the Evidence Standard before publication. Approval confirms the record is complete, coherent and consistent with the supporting material provided — it is not an audit of the client's systems.
Business outcomes: Outcome figures are recorded by the builder on the deployment or case study that produced them, and are reviewed at publication. Aggregates shown on this profile are calculated from those approved records only.
Evidence: Supporting evidence comes from the records the builder published on this platform: approved AI Deployments, published AI Case Studies, verification outcomes and organisation participation.
Currency: Older evidence continues to count and is never removed. Recency is presented separately through Professional Currency so that current expertise can be assessed alongside historical work.
Traceability: Every figure on this profile can be followed to the record that produced it. Open the linked AI Deployment or AI Case Study to read the outcome exactly as it was reported.

The platform does not independently audit client systems or financial records. How this is verified

Ready to discuss your AI implementation?

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