# Alice Labs vs Dear Future

> Comparing AI Consulting options: Stockholm vs Copenhagen. 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/alice-labs-vs-dear-future
Generated: 2026-09-17 · Curated by Gabor Kiss · No paid placements — inclusion, score, and rank are never sold.

## Facts
| | Alice Labs | Dear Future |
|---|---|---|
| Editorial score | 60/100 | 61.8/100 |
| Hourly rate | €85-130/hr (directory-listed) | not published |
| Team size | 2-9 | 50-249 |
| Location | Stockholm, Sweden | Copenhagen, Denmark |
| Founded | 2023 | 2005 |
| Last reviewed | 2026-08-05 | 2026-09-09 |
| Services | AI Consulting, AI Automation, AI Agents, AI SEO | AI SEO, AI Consulting, AI Development |
| Industries | E-commerce, Public Sector, SaaS & B2B | E-commerce, SaaS & B2B |

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

The most consistently quantified portfolio in this register, and it belongs to a firm founded in 2023.

Ljusgårda, the named client, runs a vertical farm supplying grocery stores; the SMS ordering agent built for it automates 70-80% of order calls and saves a stated 2.5 million kronor a year against an 83% cost reduction. A public-sector document process went from 60 hours to 3 minutes, freeing a claimed 6,400 to 8,000 hours annually. A media company's article rewrite engine took one page from 141 clicks to 3,091. An accounting firm went from zero to 41 top-three rankings.

Every one of those is an operational number rather than a vanity metric, which is the useful kind.

The qualification is age and attribution: one named client across five cases, two years of operating history, and no team size published. The numbers are the agency's own and none is independently verifiable. Ask for a reference call with Ljusgårda first.

### Key strengths
- Five engagements, five sets of outcome figures—no other agency on this roster publishes results this consistently
- The figures are operational: hours freed, calls automated, kronor saved, rather than impressions or engagement
- Works across automation, agents and AI search rather than one narrow service, which suits a smaller company buying its first AI project

### Good to know
- Only one of the five cases names its client—ask which sector descriptions correspond to which companies
- Founded 2023 with no published team size; confirm capacity and who would actually deliver

## Our take on Dear Future
Reviewed 2026-09-09 by Gabor Kiss against published evidence.

This is the most measured portfolio in the Copenhagen roster. For Bonnier Publications, customer data from the CRM, Google Analytics and the newsletter platform was consolidated into BigQuery, a purchase-propensity model segmented 33.3 million users into five groups, and the segments were activated directly in search and display: 53 percent growth in digital subscription sales, 18 percent higher conversion, 327 million predictions generated.

The pattern repeats at smaller scale. Atrium's course-demand model predicts registrations three months out from web activity joined to CRM and booking data, returning 45 percent better marketing performance and two to three hours a day off manual monitoring. A clinically trained chatbot for the addiction treatment center Tjele produced 354 conversations and 25 qualified calls in three months, a 14 percent conversion, against telephone inquiries falling 20 to 30 percent.

The Pandora engagement is the honest counterweight: the client had already built a customer-lifetime-value model that its national marketing teams were not using, and the work was activation and roadmapping rather than modeling.

The weaker fit is a buyer who needs a model built from research rather than from commercial data already in the stack.

### Key strengths
- Outcomes are published with the mechanism attached—33.3 million users into five segments, 327 million predictions, 53 percent subscription growth for Bonnier Publications
- The data path is named on each engagement: CRM, analytics and platform data consolidated into BigQuery before any model is trained
- Twelve case studies, every one with a named client, spanning media, retail, healthcare and education

### Good to know
- The work sits on commercial first-party data—if your problem needs a model trained on something else, ask for that engagement specifically
- The Pandora case is activation of a model the client already had; check which of your candidates' studies are modeling and which are adoption
- Trading since 2005 under a former name and rebranded recently—confirm which team carried over and who would staff you

## Which to choose
Choose Alice Labs for:
- closer collaboration at a smaller team scale
- disclosed specialization in Public Sector
- broader service offering — also covers AI Automation and AI Agents

Choose Dear Future for:
- larger team capacity for multi-stream or enterprise-scale programs
- broader service offering — also covers AI Development

## Questions buyers ask

### Which has more E-commerce experience, Alice Labs or Dear Future?
Both agencies show documented E-commerce work. Alice Labs has the broader industry stack overall, with disclosed experience in Public Sector beyond their shared focus.

### Which scores higher overall, Alice Labs or Dear Future?
Dear Future scores 61.8/100, 1.8 points higher than Alice Labs at 60/100. See our methodology for how scores are calculated.

### Which is faster to engage, Alice Labs or Dear Future?
Neither publishes lead times, so this is a read on team size rather than a measured answer. Alice Labs runs the smaller team, which usually means fewer procurement gates and a shorter path to kickoff. Dear Future 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 Alice Labs and Dear Future?
Consider running parallel discovery briefs with Alice Labs and Dear Future 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