# Faculty vs Hiflylabs > Comparing AI Consulting options: London vs 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/faculty-ai-vs-hiflylabs Generated: 2026-10-21 · Curated by Gabor Kiss · No paid placements — inclusion, score, and rank are never sold. ## Facts | | Faculty | Hiflylabs | |---|---|---| | Editorial score | 73.3/100 | 61.8/100 | | Hourly rate | not published | not published | | Team size | — | 250+ | | Location | London, United Kingdom | Budapest, Hungary | | Founded | 2014 | 2015 | | Last reviewed | 2026-08-04 | 2026-09-03 | | Services | AI Consulting, AI Development, AI Automation, AI Agents, Generative AI | AI Consulting, AI Development, AI Automation | | Industries | Public Sector, Healthcare, Legal, FinTech | FinTech, Manufacturing, Legal | ## Our take on Faculty Reviewed 2026-08-04 by Gabor Kiss against published evidence. Published case studies show systems that survived scrutiny most agencies never face—the NHS AI Lab's model-validation process for clinical AI, deployed generative-AI tooling inside Tide's support operation, and an LLM-backed recommender that now sources 25% of Axiom Law's hires. The published work index spans defense, energy, insurance, and government, though many entries are anonymized or brief. Rates are not published and the engagement profile is institutional—expect procurement-grade process rather than a lightweight pilot. The weaker fit is a small team wanting a fast, inexpensive proof of concept; this bench is built for work where failure has consequences. ### Key strengths - Published 10% ticket-handling-time reduction at Tide, with the deployed tools named (AgentAssist, MemberSummarise on Amazon Bedrock) - Applied AI since 2014 with an in-house fellowship talent pipeline—delivery here predates the LLM wave - NHS England's deputy director of AI is quoted crediting the validation work in the published study ### Good to know - Much of the work index is anonymized (military, challenger bank)—ask for a speakable reference in your sector - No published rates; budget for institutional procurement timelines ## 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 Faculty for: - closer collaboration at a smaller team scale - disclosed specialization in Public Sector / Healthcare - broader service offering — also covers AI Agents and Generative AI - a higher overall editorial score Choose Hiflylabs for: - larger team capacity for multi-stream or enterprise-scale programs - disclosed specialization in Manufacturing ## Questions buyers ask ### Which has more Legal experience, Faculty or Hiflylabs? Both agencies show documented Legal work. Faculty has the broader industry stack overall, with disclosed experience in Public Sector, Healthcare beyond their shared focus. ### Which scores higher overall, Faculty or Hiflylabs? Faculty scores 73.3/100, 11.5 points higher than Hiflylabs 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 Faculty and Hiflylabs? Consider running parallel discovery briefs with Faculty 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. --- 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