# dida vs Lautmaler

> Two top-rated AI Consulting agencies in Berlin. Side by side: published rates, team size, service and industry coverage, and the curator's assessment of both — pairings are never sold.

Canonical page: https://www.aiagencies.eu/compare/dida-vs-lautmaler
Generated: 2026-09-20 · Curated by Gabor Kiss · No paid placements — inclusion, score, and rank are never sold.

## Facts
| | dida | Lautmaler |
|---|---|---|
| Editorial score | 68/100 | 61.8/100 |
| Hourly rate | €130-175/hr (directory-listed) | not published |
| Team size | 10-49 | 10-49 |
| Location | Berlin, Germany | Berlin, Germany |
| Founded | 2018 | — |
| Last reviewed | 2026-08-04 | 2026-08-05 |
| Services | AI Consulting, AI Development, AI Automation | AI Consulting, AI Development, Generative AI |
| Industries | Manufacturing, Public Sector, Legal | SaaS & B2B, Healthcare, Public Sector |

## Our take on dida
Reviewed 2026-08-04 by Gabor Kiss against published evidence.

The Deutsche Bahn work is the most technically detailed case study on this register. dida published its approach to detecting anomalous objects on track—monocular depth estimation with a fine-tuned vision transformer, Segment Anything for masks, depth maps to rank what matters—along with before-and-after outputs and a conference talk naming the engineer who led it.

The published project index runs to roughly eighteen builds across remote sensing, industrial inspection, document understanding and public-sector search, with Deutscher Wetterdienst and Enpal among the named clients.

What the portfolio rarely states is outcomes: these are engineering write-ups, and several describe systems still in development rather than in production.

The weaker fit is a buyer who needs a business case defended in numbers—this team documents how a model works far better than what it earned.

### Key strengths
- Publishes methods at a level that can be independently assessed—named models, datasets, and the reasoning behind rejected approaches
- Works with open datasets and open publication, including a project on Deutsche Bahn's automated-driving program
- Names the scientists on its projects and runs its own annual conference, so the bench is verifiable before you engage

### Good to know
- Case studies describe method rather than result—ask for a deployed reference with numbers if you need one
- A 10-49 person team taking research-grade work; confirm capacity and timeline before committing to a deadline

## Our take on Lautmaler
Reviewed 2026-08-05 by Gabor Kiss against published evidence.

A decade of conversational AI, and the client list reads like the German enterprise directory: Telekom, VW Group, Deutsche Bahn, BVG, Merck, Gothaer, sipgate.

Two engagements are published in real depth. The sipgate chatbot is integrated across every service channel, serves customer-service agents as well as end users, and comes with a downloadable whitepaper on how it was built. YOUNA pairs a language model with a curated knowledge base to support people affected by racism, and its case study covers how the conversation is steered and how quality is measured over time—evaluation discipline, published, which is rare.

The automotive work is the longest-running: years of voice assistance for VW Group that goes past command-and-control, with an intelligent IVR concierge for Telekom in delivery.

The one gap is numbers. The public pages describe architecture and method, and the outcome figures sit inside the downloadable PDFs rather than on the page—so a buyer comparing this against an agency that publishes results openly has to go and fetch them first.

### Key strengths
- Two case studies published with genuine technical depth, including how conversation quality is measured and improved after launch
- Enterprise references at scale—Telekom, VW Group, Deutsche Bahn, BVG, Merck—across six industries rather than one
- Builds its own tooling (imPersonator for agent persona design, a Unity-to-dialog-manager bridge for XR) and partners with Cognigy and Parloa rather than reselling one platform

### Good to know
- Outcome numbers live inside downloadable PDFs rather than on the case pages—ask for them before comparing against agencies that publish openly
- No team size or founding year is published, so scale has to be established in the first call

## Which to choose
Choose dida for:
- disclosed specialization in Manufacturing / Legal
- broader service offering — also covers AI Automation
- a higher overall editorial score

Choose Lautmaler for:
- disclosed specialization in SaaS & B2B / Healthcare
- broader service offering — also covers Generative AI

## Questions buyers ask

### Which has more Public Sector experience, dida or Lautmaler?
Both agencies show documented Public Sector work and have similar industry breadth. Compare directly on the agency profiles: dida and Lautmaler.

### Which scores higher overall, dida or Lautmaler?
dida scores 68/100, 6.2 points higher than Lautmaler at 61.8/100. Both portfolio quality and business credibility feed into the score — see our methodology for the full breakdown.

### When should I consider both dida and Lautmaler?
Consider running parallel discovery briefs with dida and Lautmaler if your project spans multiple workstreams, you want competitive proposals to compare scope and approach, or you're undecided between the specialization angles each brings (see the Best for cards above). Most engagements ultimately go with one — but the parallel-brief phase is a low-cost way to validate fit.

---
Source: AIAgencies.eu — the curated register of European AI agencies. Rate provenance: "agency-confirmed" = disclosed via submission or claimed profile; "directory-listed" = Clutch or two agreeing B2B directories (lone unverified sources are never written). Full method: https://www.aiagencies.eu/methodology · Rate index: https://www.aiagencies.eu/rates