# Dmlab vs Hiflylabs

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

## Facts
| | Dmlab | Hiflylabs |
|---|---|---|
| Editorial score | 61.8/100 | 61.8/100 |
| Hourly rate | not published | not published |
| Team size | 10-49 | 250+ |
| Location | Budapest, Hungary | Budapest, Hungary |
| Founded | 2007 | 2015 |
| Last reviewed | 2026-09-09 | 2026-09-03 |
| Services | AI Consulting, AI Development | AI Consulting, AI Development, AI Automation |
| Industries | FinTech, Manufacturing, E-commerce | FinTech, Manufacturing, Legal |

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

The energy-trading system is the one to read, and it is a full operational platform rather than a model handed over. Built for Central Energy Trade Hungary Group, it collects production, consumption and weather data in real time, forecasts solar-farm output and customer demand with machine learning, trades on the power exchange against those forecasts, issues the invoices, and raises an alert when it stops behaving.

The business case is stated the way an operator states it: better forecasts mean less of the expensive balancing energy bought to cover a shortfall. The second published engagement, automated campaign-performance reporting for the Publicis-owned media agency MMS Communication, replaced a monthly Excel cycle rather than applying a model.

Eighteen years in Budapest and a client list running to Egis, Waberer's, K&H and Takarékbank, though only these two engagements are written up.

The weaker fit is a buyer who needs English-language documentation or a supplier outside Hungary, since everything here is published in Hungarian.

### Key strengths
- The energy platform is documented as an operating system, not a model: real-time ingestion, forecasting, exchange trading against the forecast, invoicing, monitoring and alerting
- The economic mechanism is named—forecast accuracy reduces the balancing energy bought to cover a shortfall—rather than left as efficiency language
- Trading since 2007, with clients across pharmaceutical manufacturing, logistics and banking on the reference list

### Good to know
- Two engagements are written up against a much longer client list—ask what was delivered for Egis, Waberer's or K&H
- Neither case study publishes a figure; ask what the forecast error was before and after, since that is where the value sits
- Everything is published in Hungarian and no rate is listed—confirm working language and pricing before scoping

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

The named LLM-era work is the reason to read the case studies: Billingo's text-to-SQL and RAG agent went from proof of concept through pilot to full production on OpenAI, Snowflake and OpenSearch with prompt anonymization via MS Presidio, and Erste Bank's agentic RAG knowledge base on LangGraph and Azure AI Search reports 200-plus documents processed and 40% higher answer accuracy.

The older classical work carries the hardest numbers—MOL Group's location-based pricing showed 3.87% gross-margin growth over a control group after six months of business-as-usual operation, and the Arconic root-cause analysis of a decade-old wheel defect ended with the line modified and the defect gone.

Two of the biggest headlines are anonymized (the 99% due-diligence cut at a global investment firm, the 2x fraud-detection accuracy at a European utility) and the Semilab and Adaptive Recognition chatbots are described as proofs of concept, so separate the deployed from the piloted when you ask for references.

The weaker fit is a buyer with a small, self-contained ML task—the studies pair the AI build with data-platform work on Databricks, Azure or Snowflake, and that is the engagement shape the firm is set up for.

### Key strengths
- Stack is listed on every study—LangGraph, MLFlow, Azure AI Search, Databricks Apps, HuggingFace, MS Presidio—so a technical buyer can check the architecture before the first call
- Third-party standing is visible: FT1000 listing, Databricks, Snowflake Select and AWS Select partner tiers, and 50-plus Databricks-certified staff per the homepage
- Named testimonials with names and titles at Catylex, MOL Group, Cirkul, Adaptive Recognition, Semilab and Billingo, and an engineering blog dated from 2020 through August 2026 with named authors

### Good to know
- The 99% analysis-time cut and the 6x ROI belong to anonymized clients—ask for a speakable reference behind each
- The homepage claims 500-plus projects and 200-plus clients against roughly 25 published case studies—ask for the list in your vertical
- Semilab and Adaptive Recognition are named proofs of concept—confirm what has run in production since, and who operates it

## Which to choose
Choose Dmlab for:
- closer collaboration at a smaller team scale
- disclosed specialization in E-commerce

Choose Hiflylabs for:
- larger team capacity for multi-stream or enterprise-scale programs
- disclosed specialization in Legal
- broader service offering — also covers AI Automation

## Questions buyers ask

### Which has more FinTech experience, Dmlab or Hiflylabs?
Both agencies show documented FinTech work and have similar industry breadth. Compare directly on the agency profiles: Dmlab and Hiflylabs.

### Which scores higher overall, Dmlab or Hiflylabs?
Both score equally well overall (61.8/100). The deciding factor is specialization — see the editorial quotes and Strengths sections above. Full methodology.

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