DeepListen · AI interview agent

100 interviews.
One AI.
A single day.

Your people take a half-hour call with an AI agent, as many at once as you need. What comes back is how your company really runs: the processes, the detours, the know-how that never left anyone's head. Once a consulting project, now a single day.

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How it works

An AI agent that listens to your whole company.

The important stuff happens between the processes: friction, delays, the cases nobody planned for. Everyone involved knows exactly what works and what doesn't, each within their own line of sight. Little of it travels upwards, and nobody sees the whole picture. DeepListen listens to every one of them and puts it together.

  1. 01

    Set the questions

    You say what you need to know. A process, a department, a problem that keeps coming back. DeepListen turns that into the interview guide.

  2. 02

    Book a time

    Your people get an invite and pick the time themselves. Whenever it fits their day. The AI always has time.

  3. 03

    Talk to the AI

    One call, half an hour. The agent listens, follows up, stays with it. A hundred conversations run at once.

  4. 04

    Get the findings

    What comes back is what used to sit scattered in people's heads. Detailed and pulled together, as a report and a process map.

The results

Conversations become a clear picture.

Not an archive of transcripts, but findings you can act on. Every one of them traces back to the conversations it came from.

The report

Many conversations. One document.

DeepListen works through every conversation one by one and brings it all together in a single document. At the top, what the leadership needs to know. Below it, the detail down to the individual step. You see the status quo at a glance and hold the groundwork that optimisation, digitalisation and AI projects build on.

The process map

The process as it actually runs

Rebuilt from every conversation: each step, each system switch, each wait, each workaround. Not the flow in the handbook, but the one people work around every day.

Process map as a swimlane diagram, reconstructed from 14 conversations
Scroll sideways for detail
The dashboard

Every conversation at a glance

Who spoke, for how long, which questions got answered, which themes came up most. Any line in the report leads straight back to the conversation behind it.

DeepListen dashboard with conversation overview, required questions and most-mentioned themes
Scroll sideways for detail
Case examples

Three cases where the answers are already in the building

Different industries, the same starting point: the people who know have never been asked systematically.

Case 01

Six figures a year for a service provider nobody can really use

Situation
A company pays a six-figure sum every year for an external fulfilment provider. Workarounds pile up across the teams, features are missing or barely documented. There are no reliable numbers on any of it.
AI interviews
Our AI agent interviews everyone who works with the system. Customer support, project management, IT. For the first time a complete picture emerges: which requirements go unmet, where people improvise, and how much time and money that actually costs.
Outcome
Management walks into the conversation with the provider carrying documented shortcomings. IT sees which gaps it can close itself in the short term.
Case 02

The most valuable knowledge in the company retires in two years

Situation
A machine builder in southern Germany has a broad portfolio and countless special cases in installation, maintenance and operation. Downtime costs its customers a great deal, so the most experienced people work in service. Their knowledge sits in their heads, not in documents. Many of them retire soon.
AI interviews
After every service call, our AI agent runs a short interview. What was broken, how was it recognisable, how does it come about, what helped.
Outcome
Out of those conversations grows a knowledge base that any colleague can still query through a chatbot years later.
Case 03

Before automation comes the question of what to automate at all

Situation
At a real-estate group, many processes still run by hand. Information gets searched for, transferred between outdated systems, special cases settled by word of mouth. The pressure to become more efficient is high. Individual AI tools have made individual employees faster, but only made the processes themselves more complex.
AI interviews
Our AI interview campaign captures the current state across departments, the way the work actually runs.
Outcome
What comes out of it is a map of the processes with clear priorities. It becomes visible what pays off immediately and where a lasting solution genuinely earns its keep.
Why conversations

The AI pressure is here, the AI effect isn't.

The licences are paid for, the copilots are live. A few people search and write a little faster. But the way you work hasn't changed. What was inefficient still is. The friction lives in your processes, and what people know about them stays in their heads.

  1. The problem

    There's no quick AI fix for everything

    AI works on top of clean processes, not in place of them. Roll it out and it exposes whatever digitalisation left behind. Without that groundwork, AI stays a glorified writing assistant.

  2. The answer

    Your best consultants are already on payroll

    Nobody knows how the work really flows better than the people doing it every day. They see where it snags, and usually how to fix it.

  3. Until now

    Tapping that know-how simply cost too much

    And it's fragile. Every time someone leaves, a piece of it goes too. Capturing it meant sitting down with every single person, which almost nobody ever did. That's exactly the part DeepListen takes over.

Local AI

Full power. Full control.

Contracts, calculations and trade secrets on US servers? That's where you lose control of both your knowledge and your costs. Today's AI prices are heavily subsidised and hinge on a policy whose rules can change overnight with new tariffs. Nobody knows what you'll pay tomorrow. On request, all our solutions run on local AI: under EU law, with predictable costs.

Cloud AI
On servers in the US or run by US companies
  • Data flows to OpenAI, Anthropic, Google & co.
  • Locked in to US providers and their pricing
  • Prices swing with arbitrary US tariff policy
  • GDPR risks with sensitive documents
Local AI
On servers under EU jurisdiction
  • Full control over your data, nothing leaves your premises
  • Runs on interchangeable hardware in EU data centres
  • Predictable costs, independent of US providers
  • GDPR-compliant, under EU law

Cloud AI is still more capable in some scenarios, and we use it where it makes sense and is safe to do so. Whenever it matters, we can move your solution fully to local AI.

The next step: a conversation.

We'll show you DeepListen live and explain how a rollout works and what comes after, with transparent costs and clear expectations. No obligation, as an equal partner.