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Shabbir Abbas's avatar
Shabbir Abbas
proEnglishtown, USA
Senior Full-Stack Engineer helping startups build Products.
$25k+
Earned
1x
Hired
4
Followers
Senior Full-Stack Engineer helping startups build Products.
Cover image for SUPERMODEL
SUPERMODEL
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24
Cover image for Marketech | Maximize your brand's revenue potential
Marketech | Maximize your brand's revenue potential
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12
Cover image for Why Choose Dealty vs. others?
Why Choose Dealty vs. others?
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14
Cover image for Lead Scout™ | Need a better Canvassing App? Look no further.
Lead Scout™ | Need a better Canvassing App? Look no further.
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11
Neo4j(1)
Łukasz Bazan's avatar
Łukasz Bazan
Głogów Małopolski, Poland
Fractional AI Architect | Deterministic GraphRAG Expert
Fractional AI Architect | Deterministic GraphRAG Expert
Cover image for NEXUS-FORGE is a proprietary Tier-0
NEXUS-FORGE is a proprietary Tier-0 architecture designed for global supply chains operating on enterprise-grade ERP systems (SAP/Oracle). This document is a redacted portfolio version of the Master Blueprint, which eliminates the risk of "Stochastic Deadlock" and API Exhaustion by implementing an Asynchronous Sidecar pattern. The primary achievement of this architecture is the transformation of unpredictable AI forecasts into a deterministic "Digital Twin" model powered by a Neo4j Knowledge Graph. This enables the prediction of cascading failures and the calculation of a logistical "Blast Radius" with mathematical precision, completely isolating core operational databases from probabilistic AI models. [ARCHITECTURAL IP & LIABILITY NOTICE] This document is a redacted sample of a Master Engineering Blueprint. It is intended exclusively for demonstrating architectural methodology and strategic framework design. It does not constitute a completed engineering source of truth for any third-party production environment. All proprietary frameworks and "Zero-Trust Fail-Safe" methodologies contained herein are the exclusive intellectual property of Łukasz Bazan. As a Fractional Architect, I provide the "Engineering Brain." I do not perform direct application coding. Any attempt to implement these patterns by internal teams is done at the Client’s own risk.
0
128
Cover image for RAMP-SENTINEL is a Tier-0 Compliance
RAMP-SENTINEL is a Tier-0 Compliance Architecture designed for the FinTech and Crypto sectors. This document is a redacted portfolio version of the Master Blueprint, showcasing an autonomous Level-2 Anti-Money Laundering (AML) investigator swarm. The primary achievement of this architecture is the elimination of the "Black-Box" liability. It replaces opaque machine learning risk scores with a transparent, deterministic graph traversal trail. By mechanically linking fiat ledgers with on-chain cryptographic data, the system drafts mathematically verified Suspicious Activity Reports (SAR) that meet the strict requirements of financial regulators (FCA, SEC, KNF). [ARCHITECTURAL IP & LIABILITY NOTICE] This document is a redacted sample of a Master Engineering Blueprint. It is intended exclusively for demonstrating architectural methodology and strategic framework design. It does not constitute a completed engineering source of truth for any third-party production environment. All proprietary frameworks and "Zero-Trust Fail-Safe" methodologies contained herein are the exclusive intellectual property of Łukasz Bazan. As a Fractional Architect, I provide the "Engineering Brain." I do not perform direct application coding. Any attempt to implement these patterns by internal teams is done at the Client’s own risk.
0
127
Cover image for LEX-SENTINEL is an advanced legal
LEX-SENTINEL is an advanced legal engineering architecture designed for high-stakes Mergers & Acquisitions (M&A). This document is a redacted portfolio version of the Master Blueprint, showcasing how to eliminate the severe legal liabilities (such as "Frankenstein Clauses") generated by probabilistic Naive RAG systems. The primary achievement of this architecture is the deployment of a Spatial Knowledge Graph. Instead of destroying document structure through standard OCR, the system maps exact (X, Y) coordinates of legal PDFs. It guarantees a 100% verifiable, Zero-Paraphrase policy, compressing cross-document liability analysis from weeks to sub-minute, mechanically verifiable audits. [ARCHITECTURAL IP & LIABILITY NOTICE] This document is a redacted sample of a Master Engineering Blueprint. It is intended exclusively for demonstrating architectural methodology and strategic framework design. It does not constitute a completed engineering source of truth for any third-party production environment. All proprietary frameworks and "Zero-Trust Fail-Safe" methodologies contained herein are the exclusive intellectual property of Łukasz Bazan. As a Fractional Architect, I provide the "Engineering Brain." I do not perform direct application coding. Any attempt to implement these patterns by internal teams is done at the Client’s own risk.
0
149
Cover image for GNOSTIC-FORGE is a Zero-Trust Code
GNOSTIC-FORGE is a Zero-Trust Code Forensic Engine designed for secure, air-gapped enterprise environments. This document is a redacted portfolio version of the Master Blueprint, demonstrating how to mitigate severe architectural debt (the "Spaghetti Cloud") without risking Intellectual Property leakage. The primary achievement of this architecture is the absolute elimination of IP exposure (Zero IP Leakage) by integrating local, secure LLMs with Abstract Syntax Tree (AST) parsing and Graph Databases. The system automates architectural governance by mechanically blocking Pull Requests that violate undocumented cross-file dependencies, compressing impact analysis time from days to parallel swarm execution. [ARCHITECTURAL IP & LIABILITY NOTICE] This document is a redacted sample of a Master Engineering Blueprint. It is intended exclusively for demonstrating architectural methodology and strategic framework design. It does not constitute a completed engineering source of truth for any third-party production environment. All proprietary frameworks and "Zero-Trust Fail-Safe" methodologies contained herein are the exclusive intellectual property of Łukasz Bazan. As a Fractional Architect, I provide the "Engineering Brain." I do not perform direct application coding. Any attempt to implement these patterns by internal teams is done at the Client’s own risk.
0
128
Neo4j(5)
Ajay Bidyarthy's avatar
Ajay Bidyarthy
Delhi, India
Data Science AI ML Expert with Python Full Stack & Backend
12
Followers
Data Science AI ML Expert with Python Full Stack & Backend
Cover image for I’ve worked on building graph
I’ve worked on building graph database solutions to handle complex, highly connected data that traditional relational databases struggle with. The main goal was to model relationships more intuitively and enable faster, more meaningful queries—especially for use cases like recommendations, fraud detection, and network analysis. Tech Stack ✔Graph Databases: Neo4j ✔Query Language: Cypher ✔Backend: Python (FastAPI / Flask) ✔Data Processing: Pandas ✔Visualization: Neo4j Bloom / D3.js ✔Cloud & Deployment: AWS / Docker
1
2
353
Cover image for I design and manage database
I design and manage database systems using Elasticsearch, Neo4j, and Supabase to enable high-speed search, rich data relationships, and scalable backend architectures. My work includes building efficient data models, optimizing performance, and ensuring secure, reliable access. I oversee the full lifecycle—from setup and integration to deployment and continuous optimization.
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254
Cover image for do database development, with supabase,
do database development, with supabase, firebase, neo4j and elasticsearch
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360
Cover image for A multi-tenant architecture is a
A multi-tenant architecture is a software architecture where a single application instance serves multiple customers (tenants) while keeping each tenant's data and configuration isolated. Example Imagine a SaaS CRM platform: - Company A uses the CRM. - Company B uses the same CRM. - Company C uses the same CRM. All three companies share the same application, but: -> Their users only see their own data. -> Their settings, branding, and permissions can be different. -> The platform provider maintains only one codebase.
2
158
Neo4j(3)
Usman Haider's avatar
Usman Haider
Lahore, Pakistan
AI/ML & Data Solutions Engineer
New to Contra
AI/ML & Data Solutions Engineer
Cover image for Retail Knowledge Graph In this project,
Retail Knowledge Graph In this project, we built a semantic knowledge graph tailored to the retail industry. The pipeline involved developing AI agents to transform heterogeneous data into standardized formats. Ontologies were created to represent domain knowledge accurately. Using Gemini models and LangChain, user queries were converted into Cypher queries to retrieve insights from a Neo4j database. We utilized an MCP server for orchestration and LangSmith for secure login and audit trails. This system enhances complex data exploration for non-technical users.
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175
Cover image for Student Medical Chatbot Built a chatbot
Student Medical Chatbot Built a chatbot to assist MBBS students in navigating medical literature. Leveraged Llama Index and fine-tuned language models to ensure accuracy. Embeddings were stored in OpenSearch, hosted on AWS. The Django backend included secure authentication and session management for a robust user experience.
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94
Cover image for Prompt Engineering Mini-Academy is a
Prompt Engineering Mini-Academy is a digital learning product built using Kajabi. It helps users learn how to write better AI prompts and use AI tools for daily tasks such as writing, research, summarization, and productivity. The problem it solves is that many people use AI tools without a proper structure, which leads to weak or generic results. This product gives users a clear learning path, practical prompt templates, and workflow examples to improve the quality of their AI outputs. I used Kajabi to create the landing page, email capture form, downloadable prompt resource, product offer, checkout page, and course structure. A sample video is attached to demonstrate the product flow and user experience.
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120
Cover image for Developed a full-stack language learning
Developed a full-stack language learning application tailored for Luxembourgish, combining speech recognition, natural language understanding, and generative AI. Fine-tuned OpenAI’s Whisper model for accurate Luxembourgish transcription and built a custom text-to-speech (TTS) engine for realistic audio feedback. A RAG-based architecture enables the app to answer user queries contextually, making learning highly interactive. The frontend is built with React, while Flask powers the backend. Designed to deliver an immersive, conversation-driven auditory learning experience.
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159
Neo4j(1)