agileful

Automating paperwork and building software for growing teams

Based in Berlin, agileful began as an agile software development shop that helped start ups and corporations turn ideas into minimum viable products. Today its site presents it as a provider of AI automation, digitalisation and custom software for growing companies, delivered by a senior team with vetted partners brought in when extra capacity is needed. It describes the shift as moving teams from chaos to calm, replacing manual steps with workflows that read, decide and act, with a person kept in the loop and results that can be audited.

AI automation for repetitive work

The automation offer covers classification, data extraction, retrieval augmented assistants and workflow automation. Examples it lists include routing and triaging email and documents, extracting data from PDFs and validating it before posting, answering repeated customer questions, searching internal knowledge on approved content, enriching and scoring sales leads, and handling CRM administration. It shows before and after flows for areas such as healthcare intake, legal enquiries, tax document processing, sales pipelines and project reporting, and says it works across industries including healthcare, legal, tax and accounting, construction, e-commerce, travel and logistics, media and education.

Digitalisation and custom software

For companies still on paper and spreadsheets, the agency turns scattered documents and emails into structured digital workflows. It also designs and ships custom software as a service platforms, web apps and mobile apps. One piece of work it highlights is digital patient intake for a multi clinic dental group, including validation, routing and integration with practice systems.

How an engagement works

The process starts by diagnosing the bottleneck and the most valuable workflow, then maps the moving parts, approvals and handoffs into a clear flow. The agency shows a future workflow quickly so teams can react early, connects inboxes, documents and internal tools into one flow, and measures outcomes before expanding to other areas. Its earlier agile practice remains visible in its methods: iterative builds based on client feedback, a dedicated team assigned to each project, and clients involved in planning decisions. It also offers machine learning models and AI driven platforms, and work migrating or building critical applications for cloud environments.