AI & Custom Automation
AI automation for document processing, lead routing and reporting
Hierarchy is an AI and automation agency based in Zurich, serving SMEs across Switzerland. We automate repetitive, rule-based processes with custom AI — from document processing to lead qualification and routing to automated reporting. You keep control over every important decision; the AI handles the volume and the busywork. That gives your team back time for the work that actually matters.
- Individual quoteafter the intro call
- 4-person team, ZürichStrategy and delivery
- 4 building blocks4 steps
Starting point
The problem: your team spends too much time on manual work
In most SMEs, valuable time goes into repetitive tasks: copying data from A to B, sorting requests, capturing documents, assembling reports. This work is necessary, but it doesn't use your people's skills. Off-the-shelf tools hit a ceiling as soon as inputs are unstructured. That's exactly where custom AI automation comes in — it understands language, documents and context, and handles the normal case reliably.
What we do
What we build
- 01
Document & invoice processing
AI reads invoices, emails and PDFs, extracts the relevant fields and passes them to your systems in a structured way — no manual retyping.
- 02
Lead routing & qualification
Incoming requests are scored, enriched and routed to the right person automatically — faster, more consistent, fully traceable.
- 03
Reporting & dashboards
Recurring reports are generated automatically from your data sources — always current, no weekly click-together.
- 04
Custom AI agents & workflows
Where standard tools fall short, we build bespoke agents and integrations that fit exactly how your business runs.
How it runs
How we work
- 01
Audit & prioritise
We map your processes and pick the lever with the biggest, fastest impact.
- 02
Build
We automate the normal case, define exceptions and connect your systems.
- 03
Human in the loop
Critical decisions and exceptions stay with your team — AI handles the volume.
- 04
Measure & scale
We measure time saved and quality, then roll out what demonstrably works.
What changes
What changes
- 01
Noticeably less repetitive work — your team focuses on what matters.
- 02
Faster, more consistent handling of requests, documents and reports.
- 03
Clear traceability: every automation is measurable and auditable.
- 04
Human in the loop — automation reduces noise, not control.
Questions
Frequently asked questions about AI Automation
What does getting started with AI automation cost?
You usually start with a single, clearly scoped process rather than a big platform. What matters is a high-volume process with a clear outcome — so the automation often pays for itself within a few months. You get a transparent estimate up front.
Which processes should we automate first?
High-volume processes with clear rules pay off fastest: document processing, lead routing, reporting and standard requests. They have low setup effort and immediately measurable impact.
Does automation replace jobs?
In practice, automation shifts work from processing volume to handling exceptions. AI takes the routine; judgement and escalation stay with people — the team is relieved, not replaced.
Is this compliant with Swiss data protection (revDSG)?
Yes, when it's built right. We rely on data minimisation, transparency, human oversight and — where needed — EU/Swiss-hosted or self-hosted models, so your data never leaves a compliant boundary.
Next step
Which process is worth automating first for you?
Tell us where manual work piles up. We'll propose a concrete first sprint — measurable and with no commitment.
About the author
Tenzin Langdun
AI Expert & Marketing Lead at Hierarchy
Tenzin is an AI expert and marketing lead with an MSc in Artificial Intelligence from the University of Bath and over 10 years of marketing experience across strategy, paid acquisition, and SEO. He has held roles at leading organisations including KPMG, EY, Siemens, and Adnovum — with expertise in AI, cybersecurity, audit and consulting, and the insurance sector. Together with Martin Oswald, he co-authored an award-winning research paper on AI-based cancer detection, published in Nature and recognised with the National Siemens Excellence Award and the Lab Sciences Award.