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Employment Reference Project: TextSenseAI

This project was developed during my two years of permanent employment at Skillbyte GmbH. The software and all associated rights are the sole property of Skillbyte GmbH. This presentation is explicitly authorized and serves purely as a portfolio showcase. I was deeply involved in the core development and took a leading role in both the conceptualization and the technical implementation of the AI architecture.

Technologies Used
Python (Core Language)
Weaviate (Vector Database)
PostgreSQL (Relational Database)
LangChain & LangGraph
Docling (Document Parsing)
FastAPI (Backend Framework)
Pydantic (Data Validation)
APScheduler (Task Scheduling)

Note: The mention of the technologies listed above is for technical documentation purposes and does not imply any business cooperation, partnership, or sponsorship by the trademark owners.

Purpose and Objectives of the Platform

TextSense centralizes internal documents and distributed expertise into an intelligent interface. The goal of the application is to eliminate manual information retrieval for teams and instead generate directly actionable answers. The developed solution is aimed at B2B companies seeking to accelerate their flow of information and sustainably streamline internal processes.

Features

Technical Implementation and Core Features:

Querying complex company knowledge using natural language.

Centralized processing of various document formats within a single knowledge base.

Context aware answers with exact references to the underlying sources.

Creation of specialized assistants for different teams and use cases.

Structured access control and implementation of approval processes.

Integration of external knowledge repositories into the search logic.