You will get a custom RAG data pipeline with pgvector
Project details
I architect and deploy custom data pipelines and Retrieval-Augmented Generation (RAG) systems for complex, domain-specific data. If you have unstructured datasets, missing identifiers, or need to bridge your proprietary databases with external literature, I build the automated infrastructure to solve it.
My signature project (Ethno-API) involved orchestrating a semantic RAG bridge over 1.55M scientific abstracts using PostgreSQL and pgvector, complete with automated validation gates.
My core stack relies on PostgreSQL (pgvector), Python-based LLM orchestration, Docker, and fault-tolerant API integrations. I deliver production-ready backend infrastructure, not experimental Jupyter notebooks.
Please message me before ordering so we can confirm your exact data schema, API rate limits, and integration requirements.
My signature project (Ethno-API) involved orchestrating a semantic RAG bridge over 1.55M scientific abstracts using PostgreSQL and pgvector, complete with automated validation gates.
My core stack relies on PostgreSQL (pgvector), Python-based LLM orchestration, Docker, and fault-tolerant API integrations. I deliver production-ready backend infrastructure, not experimental Jupyter notebooks.
Please message me before ordering so we can confirm your exact data schema, API rate limits, and integration requirements.
AI Development Type
Knowledge RepresentationAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$1,200
|
Standard
$2,400
|
Advanced
$4,200
|
|---|---|---|---|
| Delivery Time | 10 days | 14 days | 21 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | - | - | |
Detailed Code Comments | |||
Knowledge Graph | - | - | - |
Model Documentation | - | - | |
Ontology | - | - | - |
Source Code | |||
Taxonomy | - | - | - |
Frequently asked questions
About Alexander
AI Automation & Delivery Specialist | n8n, APIs, LLM Workflows
Senden, Germany - 4:37 pm local time
I help agencies and small delivery teams ship clearly scoped n8n, API, and LLM workflows. That can mean connecting systems, adding human approval, handling errors and retries, testing an existing flow, or preparing it for a clean handover. White-label delivery is possible.
Typical work:
• n8n workflow build, repair, and stabilization
• API, webhook, and database integrations
• LLM steps with separate review and human approval
• duplicate checks, retry limits, and recovery paths
• QA, test evidence, runbooks, and technical handover
Recent delivery proof:
• A running content pipeline that creates new LinkedIn drafts on different topics, separates generation from review, shows decision data in Telegram, and publishes only after human approval. Multiple approved posts were published successfully.
• MysticHerbals, a custom headless commerce MVP built with Medusa and Payload CMS.
• Ethno-API v2.4.0, a documented data and QA pipeline with 76,907 records.
Best fit: you already have a defined workflow or bottleneck and need one delivery slice finished, stabilized, or handed over cleanly.
Send me the target, the systems involved, the current blocker, and the acceptance criterion. I will tell you directly whether the scope fits.
Steps for completing your project
After purchasing the project, send requirements so Alexander can start the project.
Delivery time starts when Alexander receives requirements from you.
Alexander works on your project following the steps below.
Revisions may occur after the delivery date.
Pipeline Architecture & Integration
I design and deploy the core data infrastructure. This includes setting up PostgreSQL with pgvector for semantic search, orchestrating LLM agents, and integrating required external APIs to clean and enrich your raw data.
Testing & Handover
Rigorous validation and QA runs to ensure data integrity and pipeline stability. Once verified, I securely hand over the production-ready database, integration scripts, and complete documentation for your internal team.