Lauren Santiago
Atlanta, United States
AI-Ready Data Pipelines | RAG Architecture & Enterprise Data Integration
(0) Remote 2 months ago
150 $ - Per hour
The Problem:
Generic AI is powerful, but it doesn't know your business. Most companies struggle to feed their internal documents, SQL databases, and legacy "MuleSoft" data into AI models without hitting security walls or getting "hallucinations." If your data isn't structured for AI, the AI is useless.
The Solution:
I build the "Secure Data Bridge" between your company’s private information and modern AI models (OpenAI, Anthropic, or Private LLMs). Using Retrieval-Augmented Generation (RAG) architecture, I ensure your AI has real-time access to your specific data—whether it lives in SharePoint, a PostgreSQL database, or a healthcare EHR.
What I Deliver:
• Data Extraction & Cleaning: Building robust pipelines in Java or .NET to pull and "clean" data from siloed systems.
• Vector Database Setup: Implementing and managing vector stores (like Pinecone, Weaviate, or Azure AI Search) so your data is "searchable" by AI.
• API Middleware: Creating secure MuleSoft or Node.js connectors that act as the gatekeeper between your data and the AI.
• Accuracy Tuning: Optimizing how data is "chunked" and indexed to ensure the AI provides precise, context-aware answers every time.
• Enterprise Security: Implementing OAuth 2.0 and Role-Based Access Control (RBAC) so the AI only "sees" what the specific user is authorized to see.
High-Impact Use Cases:
• Internal Knowledge Bots: An AI that can answer complex questions about your company’s 10-year-old SOPs or technical manuals.
• Automated Data Mapping: Using AI to automatically translate legacy data formats (like old flat files) into modern FHIR or JSON structures.
• Smart Customer Support: Feeding your live ticketing data into an AI agent to resolve 60% of common queries instantly.
🛠️ Technical Stack
• Languages: Java/J2EE, Python, .NET C#
• Integration: MuleSoft, REST/GraphQL, Kafka
• AI Tools: LangChain, LlamaIndex, OpenAI API, Anthropic Claude
• Databases: PostgreSQL (pgvector), Pinecone, MongoDB, SQL Server
💰 Pricing & Engagement
• AI Readiness Audit: $2,500 (Mapping your data sources and creating an AI-implementation roadmap).
• Pipeline Implementation: $150/hr or project-based starting at $7,500.
• Retainer: $2,000/mo for ongoing pipeline maintenance and model fine-tuning.
Generic AI is powerful, but it doesn't know your business. Most companies struggle to feed their internal documents, SQL databases, and legacy "MuleSoft" data into AI models without hitting security walls or getting "hallucinations." If your data isn't structured for AI, the AI is useless.
The Solution:
I build the "Secure Data Bridge" between your company’s private information and modern AI models (OpenAI, Anthropic, or Private LLMs). Using Retrieval-Augmented Generation (RAG) architecture, I ensure your AI has real-time access to your specific data—whether it lives in SharePoint, a PostgreSQL database, or a healthcare EHR.
What I Deliver:
• Data Extraction & Cleaning: Building robust pipelines in Java or .NET to pull and "clean" data from siloed systems.
• Vector Database Setup: Implementing and managing vector stores (like Pinecone, Weaviate, or Azure AI Search) so your data is "searchable" by AI.
• API Middleware: Creating secure MuleSoft or Node.js connectors that act as the gatekeeper between your data and the AI.
• Accuracy Tuning: Optimizing how data is "chunked" and indexed to ensure the AI provides precise, context-aware answers every time.
• Enterprise Security: Implementing OAuth 2.0 and Role-Based Access Control (RBAC) so the AI only "sees" what the specific user is authorized to see.
High-Impact Use Cases:
• Internal Knowledge Bots: An AI that can answer complex questions about your company’s 10-year-old SOPs or technical manuals.
• Automated Data Mapping: Using AI to automatically translate legacy data formats (like old flat files) into modern FHIR or JSON structures.
• Smart Customer Support: Feeding your live ticketing data into an AI agent to resolve 60% of common queries instantly.
🛠️ Technical Stack
• Languages: Java/J2EE, Python, .NET C#
• Integration: MuleSoft, REST/GraphQL, Kafka
• AI Tools: LangChain, LlamaIndex, OpenAI API, Anthropic Claude
• Databases: PostgreSQL (pgvector), Pinecone, MongoDB, SQL Server
💰 Pricing & Engagement
• AI Readiness Audit: $2,500 (Mapping your data sources and creating an AI-implementation roadmap).
• Pipeline Implementation: $150/hr or project-based starting at $7,500.
• Retainer: $2,000/mo for ongoing pipeline maintenance and model fine-tuning.
Please sign in as a customer to give your feedback
