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AI-Driven Reputation Intelligence for Fashion Talent & Campaigns

AI-Driven Reputation Intelligence for Fashion Talent & Campaigns

Media
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We built a reputation intelligence system that turns the open web into a structured, searchable signal for fashion brands and talent teams. The platform…

Universal Data Ingestion Pipeline for GenAI & RAG

Universal Data Ingestion Pipeline for GenAI & RAG

Media
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We built a universal data ingestion and knowledge pipeline that can take almost any type of file – PDF, Excel, XML, JSON, images, audio,…

Media

AI-Driven Reputation Intelligence for Fashion Talent & Campaigns

We built a reputation intelligence system that turns the open web into a structured, searchable signal for fashion brands and talent teams. The platform…

  • Strategy

    Unify web-scale collection with entity resolution and narrative analytics so teams can move from detection to decision quickly, with traceability to source content.

  • Design

    Streaming and batch ingestion into a lakehouse foundation, AI services for entity linking and sentiment/theme extraction, and an operational interface with alerting, review, and reporting workflows.

  • Client

    Fashion brands, agencies, and campaign teams operating across EU and global markets.

  • Tags

    analytics, entity-resolution, fashion, monitoring, nlp, reputation, risk, web-crawling

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Media

Universal Data Ingestion Pipeline for GenAI & RAG

We built a universal data ingestion and knowledge pipeline that can take almost any type of file – PDF, Excel, XML, JSON, images, audio,…

  • Strategy

    Standardised ingestion layer for all file types, schema-agnostic knowledge model, multi-backend storage strategy (SQL, vector, graph), optimisation for RAG and agent retrieval patterns, and built-in observability for quality and governance.

  • Design

    Modular processors for PDFs, spreadsheets, XML/JSON and multimedia (OCR and speech-to-text), enrichment services for embeddings, summarisation and entity extraction, pluggable storage adapters for relational, vector and graph databases, and orchestration that exposes the final knowledge layer to GenAI agents, chatbots and analytics tools.

  • Client

    Media company from Germany (EU)

  • Tags

    data ingestion, data lake, data processing, graph db, RAG, vector db

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