# dida vs Ultra Tendency

> 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-ultra-tendency
Generated: 2026-09-17 · Curated by Gabor Kiss · No paid placements — inclusion, score, and rank are never sold.

## Facts
| | dida | Ultra Tendency |
|---|---|---|
| Editorial score | 68/100 | 65.8/100 |
| Hourly rate | €130-175/hr (directory-listed) | not published |
| Team size | 10-49 | 50-249 |
| Location | Berlin, Germany | Berlin, Germany |
| Founded | 2018 | 2010 |
| Last reviewed | 2026-08-04 | 2026-09-09 |
| Services | AI Consulting, AI Development, AI Automation | AI Development, AI Consulting, Generative AI |
| Industries | Manufacturing, Public Sector, Legal | Manufacturing, FinTech, 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 Ultra Tendency
Reviewed 2026-09-09 by Gabor Kiss against published evidence.

The European Central Bank engagement is the one that settles the credibility question. SPACE, the statistical production platform replacing a twenty-five-year-old system, takes KPI submissions from every eurozone national central bank and carries more than a thousand data scientists and statisticians working in parallel. Ultra Tendency states it is wholly responsible for the architecture, the implementation and the testing, with ninety-six business processes migrated alongside T-Systems, on HBase, Kafka, Spark and Kubernetes.

The HUK-COBURG telematics platform has run since 2016 for Germany's largest motor insurer, on Cloudera clusters with an active-active second site and traffic spikes absorbed by AWS. The insurer's own DevOps lead is quoted saying there has not been a single service interruption since implementation, which is a client-side claim rather than a supplier one.

Read the portfolio for what it actually is. This is data platform and streaming engineering—ingestion, clusters, migration, monitoring—and the published work does not describe a model, an evaluation or an accuracy figure anywhere.

Best for institutions buying the data layer underneath analytics at a scale where downtime is the risk, rather than a team to build and validate models on top of it.

### Key strengths
- The European Central Bank platform is described with scope attached: wholly owned architecture and testing, ninety-six migrated business processes, and every eurozone national central bank feeding it
- Client-side people are quoted by name at HUK-COBURG and Vattenfall, including the insurer's DevOps lead on uninterrupted service since 2016
- The Vattenfall engagement includes training so the client's own teams can run the platform, with the migration designed for zero downtime and the old cluster retired

### Good to know
- The published case studies are data infrastructure—no model, evaluation or accuracy figure appears in any of them; ask for a machine-learning engagement specifically
- Headquarters is Colbitz with Berlin as one of several offices—confirm which office staffs your engagement and in which time zone
- No team page, headcount or rate is published; ask who the named architects are on a platform you expect to run for years

## Which to choose
Choose dida for:
- closer collaboration at a smaller team scale
- disclosed specialization in Legal
- broader service offering — also covers AI Automation
- a higher overall editorial score

Choose Ultra Tendency for:
- larger team capacity for multi-stream or enterprise-scale programs
- disclosed specialization in FinTech
- broader service offering — also covers Generative AI

## Questions buyers ask

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

### Which scores higher overall, dida or Ultra Tendency?
dida scores 68/100, 2.2 points higher than Ultra Tendency at 65.8/100. Both portfolio quality and business credibility feed into the score — see our methodology for the full breakdown.

### Which is faster to engage, dida or Ultra Tendency?
Neither publishes lead times, so this is a read on team size rather than a measured answer. dida runs the smaller team, which usually means fewer procurement gates and a shorter path to kickoff. Ultra Tendency runs a larger one, which tends to mean more steps but more capacity to start parallel workstreams. Current kickoff availability is the number that actually decides it — ask both.

### When should I consider both dida and Ultra Tendency?
Consider running parallel discovery briefs with dida and Ultra Tendency 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.

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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