Enterprise AI Data Fusion Platform Development
Publicada el 2026-07-22
Descripción de la oferta
Project Description Overview We are building a large-scale Enterprise AI Data Fusion Platform capable of integrating multiple structured and unstructured data sources into a unified analytics environment. The platform will leverage modern AI, graph analytics, geospatial visualization, machine learning, natural language processing, and advanced search technologies to deliver actionable insights from large datasets. This is a greenfield project with a long-term roadmap. We are seeking highly experienced software architects and senior AI engineers capable of designing scalable, enterprise-grade systems. ________________________________________ Core Capabilities AI-Powered Search • Natural language search • Semantic search • Entity lookup • Context-aware retrieval • Intelligent filtering ________________________________________ Entity Resolution Merge records from multiple independent datasets into unified entity profiles. Examples include: • customer records • organizational records • assets • locations • devices • documents ________________________________________ Knowledge Graph Interactive relationship visualization including: • entity relationships • organizational hierarchies • asset relationships • event timelines • network analysis ________________________________________ AI Assistant Enterprise AI assistant capable of: • summarizing information • generating reports • answering questions over internal datasets • identifying patterns • recommending next actions ________________________________________ Document Intelligence • OCR • PDF processing • document classification • entity extraction • knowledge extraction ________________________________________ Geospatial Analytics Interactive mapping Historical movement visualization Heatmaps Location clustering Route visualization Geofencing ________________________________________ Predictive Analytics Machine learning models for: • anomaly detection • trend prediction • behavioral analysis • pattern recognition • forecasting ________________________________________ Dashboard Modern executive dashboard including: • KPIs • alerts • analytics • reporting • visualization • customizable widgets ________________________________________ Preferred Technology Backend • Python • FastAPI • PostgreSQL • Neo4j • Elasticsearch • Redis • Kafka AI • PyTorch • TensorFlow • LangChain • Llama • Vector Databases • RAG Frontend • React • TypeScript • Mapbox • D3.js or Cytoscape.js Infrastructure • Docker • Kubernetes • AWS or Azure • CI/CD ________________________________________ Deliverables • Production-ready source code • Complete documentation • API documentation • Database design • Deployment scripts • Testing • Docker containers • Security best practices • Technical documentation ________________________________________ Who We're Looking For Senior engineers with experience building: • Enterprise SaaS platforms • AI applications • Knowledge graphs • Big data platforms • Large-scale search systems • Distributed systems • Analytics platforms • Cloud-native microservices Here's a practical budget allocation. Role / Deliverable Duration Budget (USD) Solution Architect / Technical Lead Part-time (8–10 weeks) $6,000 Senior Backend Engineer (Python/FastAPI) Full-time $10,000 AI / Machine Learning Engineer Full-time $9,000 Frontend Engineer (React/TypeScript) Full-time $7,000 DevOps & Cloud Engineer Part-time $4,000 UI/UX Designer Contract $2,000 QA / Test Engineer Contract $2,000 Security Review & Penetration Testing Final phase $3,000 Project Management & Contingency Throughout $7,000 Total $50,000 Suggested Milestone Payments Milestone 1 – Planning & Architecture (10%) – $5,000 • Technical architecture • UI/UX wireframes • Database schema • API specifications • Project roadmap Milestone 2 – Core Platform (20%) – $10,000 • Authentication • User management • Backend framework • Database setup • Initial frontend Milestone 3 – Data & Search (25%) – $12,500 • Data ingestion pipelines • Search capabilities • Entity management • Knowledge graph integration Milestone 4 – AI Features (25%) – $12,500 • AI assistant • Document processing • Analytics • Reporting • Dashboard Milestone 5 – Deployment & Acceptance (20%) – $10,000 • Testing • Security review • Performance optimization • Documentation • Deployment • Bug fixes Team Structure To stay within budget, keep the core team lean: • 1 Solution Architect / Technical Lead • 1 Senior Backend Engineer • 1 AI / ML Engineer • 1 Frontend Engineer • 1 DevOps Engineer (part-time) • 1 UI/UX Designer (contract) • 1 QA Engineer (contract) This is a 6–7 person team, with only three to four people working full-time at any given point. Scope Expectations A $50,000 budget is realistic for delivering: • Secure authentication and role-based access • Modern web interface • Data ingestion framework • Search and entity resolution • Knowledge graph visualization • AI-powered document summarization and Q&A over ingested data • Interactive dashboards • Containerized deployment and documentation Please include portfolio links, GitHub repositories, architecture examples, and previous enterprise projects. ________________________________________ Important Shortlisted candidates will be required to sign a Non-Disclosure Agreement (NDA) before detailed functional requirements are shared
Skills
- FastAPI
- Python
- Neo4j
- Machine Learning
- D3.js
- Data Warehousing
- Data Analytics
- Rust
- Project Management
- PostgreSQL
- Kubernetes
- TensorFlow
- PyTorch
- Docker
- UI/UX Design
- Presupuestos
- React
- Azure
- AWS
- QA Testing
Fuente original: freelancer