Applied AI

Applied AI for automation, search and better decisions.

Useful AI does not start with an isolated demo. It starts with concrete processes, available data, clear limits and a way to measure whether the system helps.

Discuss an AI project

Internal assistants and copilots

  • Assistants for support, operations, sales or back office functions.
  • Connection to internal documentation, tickets, CRM or ERP.
  • Answers with sources, confidence boundaries and human escalation.

RAG and semantic search

  • Indexing documents, knowledge bases and technical content.
  • Hybrid search across text, vectors and metadata.
  • Permission control, traceability and incremental updates.

Document extraction and classification

  • Processing PDFs, emails, invoices, delivery notes, contracts or forms.
  • Structured extraction with human validation where needed.
  • Classification, tagging and routing of documents or requests.

Process automation

  • Review, summarization, prioritization and draft-generation flows.
  • Integration with n8n, queues, APIs, webhooks and internal tools.
  • Controls to avoid high-risk automated actions without approval.

Evaluation, safety and operations

  • Test sets, quality metrics and regression checks.
  • Logging of prompts, answers, sources and errors.
  • Safety controls, privacy, usage cost and monitoring.

Applied AI

Typical deliverables

Validated prototype with real data Integration architecture Ingestion and update pipeline n8n workflow where useful Evaluation dashboard Deployment and operating documentation