
5
5
1 year of experience
My name is Yousun Lotif, and I am an engineer specializing in Computer Science and Engineering (CSE). I have a strong interest in technology, software development, and solving real-world problems through innovative solutions. I am continuously learning and expanding my skills to stay updated with the latest trends in the tech industry.

OmniSignal AI is an Enterprise Live Web Intelligence Command Center that turns public web data into actionable business intelligence. Enterprises constantly miss important external signals because useful information is scattered across vendor websites, pricing pages, public RFP portals, competitor announcements, security advisories, regulatory updates, and public documents. These signals can reveal supplier risk, pricing changes, contract exposure, compliance impact, market movement, savings opportunities, and new revenue opportunities. OmniSignal AI solves this by creating a unified intelligence layer powered by a Bright Data-style web ingestion pipeline. The workflow is simple: Bright Data unlocks public web data, OmniSignal AI collects and structures signals, AI scores risk and opportunity impact, the dashboard shows business intelligence, AI Copilot explains what matters, and workflows plus integrations turn insights into action. The platform includes a Command Center, Signals Intel, Vendor Risk Intelligence, Opportunities, Risk & Compliance, Markets & Competitors, Contracts & Renewals, Savings Analyzer, AI Copilot, Sources, Workflows, and Integrations. Users can analyze text, URLs, websites, company names, or document references and generate AI summaries, severity scores, confidence levels, recommended actions, and downloadable reports. The current version is a hackathon MVP with a working React frontend, FastAPI backend, dynamic API routes, Bright Data demo/live mode structure, AI Copilot, module-specific AI analysis, report exports, workflow simulation, and integration concepts. In production, the system can connect real Bright Data APIs, add persistent storage, real file parsing, scheduled monitoring, LLM reasoning, authentication, audit logs, and real enterprise integrations such as Slack, Salesforce, Jira, ServiceNow, Snowflake, Coupa, and Microsoft Teams.
31 May 2026

NeuroSentinel is a secure AI agent governance and trust platform designed for enterprise environments. It allows AI agents to safely interact with company documents, answer questions, and perform actions while mitigating risks such as sensitive data leaks, unauthorized access, prompt injection, policy violations, hallucinations, and unsafe tool usage. Key modules include intent mismatch detection, PolicyGuard decision engine, SafeTool sandbox, AI evidence locker, human-in-the-loop approval, auto-remediation, kill switch, and business impact dashboards. By enforcing real-time security checks, audit logging, and governance controls, NeuroSentinel ensures AI agents operate reliably, compliantly, and transparently, giving enterprises confidence to deploy AI safely.
19 May 2026

CodeSentinel by Yousun is an IBM Bob-powered codebase intelligence and release-readiness platform designed to help developers understand code faster, reduce repetitive work, and ship software with confidence. Modern software teams often struggle with unfamiliar repositories, risky files, missing tests, outdated documentation, unclear pull request impact, and release uncertainty. CodeSentinel solves this by using IBM Bob as the AI intelligence layer. IBM Bob analyzes repository or code context and produces structured insights, while CodeSentinel turns those insights into a clean dashboard, actionable modules, and downloadable PDF reports. The platform supports three input modes: Repository URL, Code Doc, and IBM Bob Output. Its main modules include Risk Radar + Bug-to-Test, Documentation + Junior Rescue Mode, PR Impact + Repo Time Machine, Architecture Drift, Test Intelligence, and Release Readiness. CodeSentinel helps teams move from unknown codebase to clear insight, action plan, and safer release.
17 May 2026

NeuroSentinel is an AI agent security and governance platform designed to help enterprises use AI safely with sensitive internal documents and business workflows. As companies adopt AI agents for document analysis, email drafting, knowledge search, and decision support, security risks become a major concern. AI agents may access confidential files, expose restricted information, send unsafe emails, or take actions without proper approval. NeuroSentinel solves this problem by acting as a security layer between enterprise users, internal documents, AI agents, and communication systems. The platform enforces strong Identity and Access Management (IAM) and Role-Based Access Control (RBAC), so every user and AI agent can only access the documents, tools, and actions they are authorized to use. It checks company policies before allowing AI-generated actions, controls secure email behavior, records detailed audit evidence, and requires human approval for sensitive decisions. This makes AI usage more transparent, compliant, and trustworthy. NeuroSentinel is especially useful for organizations that handle confidential data, such as legal teams, HR departments, finance teams, healthcare organizations, and enterprise operations. Instead of blocking AI adoption, NeuroSentinel enables safe AI adoption by combining automation with governance. It gives enterprises the confidence to use AI agents while maintaining security, accountability, and control. In simple terms, NeuroSentinel helps companies unlock the power of AI without losing control over their data, policies, or trust.
19 May 2026

RocGenesis is an AMD-ready AI Development Copilot designed to help developers move from raw idea to deployment-ready AI applications with more confidence. Developers working with GPU-powered AI projects often face many challenges: planning the project architecture, setting up AMD/ROCm workflows, generating safe terminal commands, understanding ROCm/PyTorch/HIP errors, estimating GPU memory usage, checking safety risks, and preparing final documentation. These steps are usually handled separately, which slows down development and increases the chance of mistakes. RocGenesis brings these steps into one guided dashboard. The Design & Build Flow generates an AMD-ready project blueprint from a raw idea. CommandFlow creates safe setup, run, test, and deployment command runbooks. DebugFix analyzes ROCm, HIP, and PyTorch errors with root cause, fixed code, validation commands, and safety score. GPU Estimate predicts VRAM usage, out-of-memory risk, AMD GPU fit, and optimization strategies. Safety Guard scans code, commands, secrets, dependencies, and unsafe patterns. The Reports module generates judge-ready project documentation and deployment evidence. The project is built with Python, Streamlit, Qwen through OpenRouter API, and Hugging Face Spaces. RocGenesis is especially focused on AMD AI developers by supporting ROCm-aware setup guidance, HIP/ROCm error reasoning, AMD GPU workload estimation, and deployment readiness. RocGenesis helps developers build, debug, optimize, secure, and ship AI apps on AMD GPUs from one professional AI-assisted workflow.
10 May 2026