Real experience. Direct delivery.
No account managers, no handoffs to junior staff. You talk to the person who builds it - from the first call to the final handover.
Sandis
More than fifteen years in enterprise IT - platform ownership, process design, compliance programmes across global organisations. For the last few years, I've been building AI systems: knowledge bases, agent workflows, automation pipelines.
I work with Claude, n8n, Make.com, OpenAI, Gemini, Python - whatever fits the problem. The tooling comes after the business logic and the data quality.
Baiba
More than ten years in finance - accounting, financial reporting, and multi-region operations across fintech and professional services. Currently also leading AI adoption for finance teams - internal Claude AI and Claude Cowork training programmes, Power BI analytics across multiple markets, and practical AI integration in finance operations.
I'm the one asking 'will this actually work inside a real finance team?' - and that question changes a lot of what we build. My role at DigiDuo is the finance and analytics angle, and the reality check.
What We Do
We work at the intersection of business process knowledge and practical AI development. Most people are strong on one side or the other - we cover both.
- Process and data first - we check whether your process is well-defined and your data is good enough before any AI or automation. A lot of projects fail here, and we'd rather say that upfront.
- AI agents - for document processing, communication, classification, or decision support. Built to run reliably, not just to demo well.
- Automation - connecting tools, eliminating manual steps, building reporting pipelines. Often the right answer before AI enters the picture.
- Finance and analytics - reporting structures, BI dashboards, accounting process improvements. Baiba's background means we engage with the financial logic directly.
- AI knowledge base - structuring your company context, processes, and rules so every AI system draws from one accurate foundation. Build once, improve everything.
How We Approach Problems
We don't arrive with the answer already chosen. We ask questions, look at your data and tools, and figure out what's actually causing friction - and what AI could make practical that wasn't before.
We'll present a few options: what's quick, what's more robust, what's worth doing first. You choose. We give you our honest recommendation.
We're not tied to any vendor. We recommend what fits - Claude, OpenAI, Gemini, n8n, Make.com, Power BI, and others depending on the situation.
What to Expect
You'll always talk to one of us directly. We document everything and aim to leave you independent. We'll also tell you honestly when something isn't worth doing, when AI isn't the right tool, or when a process problem needs sorting before automation will help.