Data pipelines and analytics

LLM-powered data cleaning, enrichment, and insight generation from unstructured or messy data sources.

A lot of valuable data is messy - free text, inconsistent formats, scattered across spreadsheets and emails. LLMs can clean, normalise, enrich, and extract insights from unstructured data in ways that traditional ETL struggles with.

I build pipelines that ingest your messy data, apply AI for cleaning and enrichment, and output structured data for analytics or downstream systems. Use cases include: normalising product or customer data, extracting entities from notes or feedback, generating summaries for reporting, or enriching records with external context. For Barnsley businesses with legacy data or manual data entry, this often unlocks analytics that weren't feasible before.

Example AI integrations

AI services and tools I've integrated for Barnsley businesses include:

Unstructured.io

AI-powered parsing of PDFs and docs for LLM ingestion. For data pipelines, it ingests messy documents and outputs structured data for analytics.

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Pandas AI

Natural language to dataframe queries via LLM. For data pipelines, it lets analysts query and clean data using natural language.

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LangChain

Document loaders and chains for data extraction and enrichment. For data pipelines, it chains loaders and LLMs for extraction and enrichment.

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LangSmith

LLM observability, tracing, and evaluation for AI pipelines. For data pipelines, it traces and debugs LLM runs and evaluates outputs.

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Haystack

NLP framework for LLM pipelines and document processing. For data pipelines, it builds document processing and extraction pipelines.

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Ragas

AI evaluation and benchmarking for RAG pipelines. For data pipelines, it evaluates and benchmarks RAG and extraction quality.

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Types of Barnsley businesses I work with on AI

  • Manufacturing and engineering - Process documentation, quality checks, supplier comms, and internal knowledge bases. Often starting with one high-friction workflow.
  • Healthcare and life sciences - Clinical documentation, medical records, research automation, and compliance for healthcare providers.
  • Professional services - Law, accountancy, consulting. Document review, contract extraction, client intake, and research automation.

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