# Dashbouquet vs MindTitan

> Two top-rated AI Development agencies in Tallinn. 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/dashbouquet-vs-mindtitan
Generated: 2026-09-17 · Curated by Gabor Kiss · No paid placements — inclusion, score, and rank are never sold.

## Facts
| | Dashbouquet | MindTitan |
|---|---|---|
| Editorial score | 51/100 | 64/100 |
| Hourly rate | €45-85/hr (directory-listed) | €45-85/hr (directory-listed) |
| Team size | 50-249 | 10-49 |
| Location | Tallinn, Estonia | Tallinn, Estonia |
| Founded | 2014 | 2016 |
| Last reviewed | 2026-09-03 | 2026-09-10 |
| Services | AI Development, Generative AI, AI Consulting | AI Consulting, AI Development, AI Agents, AI Automation |
| Industries | Healthcare, SaaS & B2B, E-commerce | Public Sector, FinTech, SaaS & B2B |

## Our take on Dashbouquet
Reviewed 2026-09-03 by Gabor Kiss against published evidence.

The AI evidence splits into two kinds: production-scale data extraction—Dashmote's beverage-menu platform pulled menus from 10,000-plus venues across 45-plus countries in 12 languages, processing 100 GB a day on AWS, Kubernetes, Argo Workflows, SpaCy and PyTorch over 16 months—and early LLM product work, where BetterYou's therapist dashboard and a dating-assistant app document model bake-offs (GPT-4, Claude 3, Llama 3, Mixtral) but publish no usage or accuracy figures.

That split is a buyer consequence: the extraction and BI systems (a second one tracked 21,000 SKUs across 9 marketplaces for 18 months) show a team that keeps scrapers and parsers alive against layout changes, while the LLM studies read as pre-product builds, so if your brief is a generative feature in production, ask what happened after launch.

The strongest outcome on the site is not an AI one—Pyroscope credits the firm with a 2x revenue lift and 30% more daily active users before its acquisition by Grafana Labs—which counts as a delivery signal and not as an AI signal.

The weaker fit is buyers who need a model team rather than a product team—the published work puts LLMs and OCR inside apps the firm also builds, with no study where the model itself was the deliverable.

### Key strengths
- Team composition and duration are published per data project (2 engineers, 2 analysts, 1 PM over 16 and 18 months), so you can size a comparable engagement
- Sprint rhythm is stated and consistent across the site: features every 1–3 weeks, two-week demos, and a Clutch 1000 listing for 2025
- Pyroscope's CEO reviews the firm by name on Clutch, and the collaboration is described down to the Node.js and Ruby profiling agents delivered

### Good to know
- Ask what became of the BetterYou and dating-assistant builds after handover—both studies stop at model selection with no adoption or accuracy numbers
- Confirm who leads the ML work: the about page names no engineers, and the AI services page lists Caffe, Theano and CNTK among its platforms, which are years out of maintenance
- The AI services page positions the firm around OpenAI-style APIs—if you need a fine-tuned or self-hosted model, ask for a reference beyond the SpaCy and OCR extraction work

## Our take on MindTitan
Reviewed 2026-09-10 by Gabor Kiss against published evidence.

The published work is machine learning delivered into operations and then measured, which is rarer than the category's marketing suggests. Elisa's customer service bot Annika, live since 2017, handles up to 70% of inbound contacts and fully resolves 42% of what it takes, so roughly a third of all contacts close without a person.

The Hepta Airborne engagement is the one that shows engineering character rather than results: computer vision finding defects on power lines inside the client's own inspection platform, with the write-up admitting that no usable public dataset existed, that the team had to build and label one, and that the models took a long time to get right.

Client staff are quoted by name in both, and the Hansab work puts a number on a dull, real problem—at least 10% fewer trips to refill ATMs.

The weaker fit is a buyer wanting a language-model product shipped this quarter: the pattern here is a measured system built end to end, which takes longer and holds up better.

### Key strengths
- Outcomes are stated in operational terms with the denominator attached—contacts handled, contacts resolved, refill trips avoided—rather than as accuracy scores nobody outside the team can interpret
- The published record spans conversational AI, computer vision, forecasting and recommendation work, so the practice is not one technique repackaged
- Case studies are candid about what was hard, including missing training data and long model development, which is a fair preview of how scoping conversations will go

### Good to know
- The flagship deployment dates from 2017 and predates current language models—ask what has been built on modern stacks and what is running today
- No team page or headcount is published despite delivery being described as in-house—ask how many engineers would be on your project and where they sit
- MindTitan publishes no rate itself; the €45-85/h shown here comes from a third-party directory listing

## Which to choose
Choose Dashbouquet for:
- larger team capacity for multi-stream or enterprise-scale programs
- disclosed specialization in Healthcare / E-commerce
- broader service offering — also covers Generative AI

Choose MindTitan for:
- closer collaboration at a smaller team scale
- disclosed specialization in Public Sector / FinTech
- broader service offering — also covers AI Agents and AI Automation
- a higher overall editorial score

## Questions buyers ask

### Which is cheaper, Dashbouquet or MindTitan?
Pricing is comparable: Dashbouquet at €65/hr median vs MindTitan at €65/hr. Choose on specialization rather than cost.

### Which has more SaaS & B2B experience, Dashbouquet or MindTitan?
Both agencies show documented SaaS & B2B work and have similar industry breadth. Compare directly on the agency profiles: Dashbouquet and MindTitan.

### Which scores higher overall, Dashbouquet or MindTitan?
MindTitan scores 64/100, 13 points higher than Dashbouquet at 51/100. See our methodology for how scores are calculated.

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