Process automation
Repetitive flows on documents, emails, tickets, content. Less manual work, more consistency.
Applied AI
AI in production, not in slides.
Applied AI where it generates value: automations, knowledge-base assistants, product features. Models picked on cost and quality, not on hype.
Where we use it well
Internal assistants with RAG
Chatbots on your knowledge base: manuals, procedures, past projects. Answers sourced from your data.
AI features inside digital products
Classification, generation, summarization, suggestions. Integrated into real UI, measured.
Feasibility assessment
If AI doesn't make sense here, we tell you. We don't run AI projects that only generate cost.
Stack and models
APIs from the main providers (OpenAI, Anthropic, Google) and open-source models when local hosting makes sense. Vector DB, RAG pipeline, eval framework. Model choice is cost-vs-quality, not hype.
How we work
- 01Before writing code: define success and the metric
- 02Prototype in two weeks or less
- 03Evals and benchmarks before go-live
- 04Quality monitoring post-deploy
Frequently asked
Before you write an email.
Thirty minutes to clarify scope, timing, and investment range.
Thirty minutes, no sales slides. We figure out together whether we're the right partner.