# Damavis > Damavis is a reviewed AI agency in Madrid, Spain, listed in the AIAgencies.eu register and last assessed 2026-09-20. Canonical page: https://www.aiagencies.eu/agency/damavis Generated: 2026-09-21 · Curated by Gabor Kiss · No paid placements — inclusion, score, and rank are never sold. ## Facts - Location: Madrid, Spain - Website: https://damavis.com - Hourly rate: not published - Team size: 10-49 - Founded: 2018 - Services: AI Development, AI Consulting - Industries: E-commerce - LinkedIn: https://www.linkedin.com/company/damavis ## About Damavis is a big-data and machine-learning studio with Madrid and Palma offices building data lakes, models and real-time pipelines for data-driven companies. ## Documented clients Documented engagements: Meliá Hotels International, Hotelbeds, and Camper. All 3 carry a source URL on file. ## Curator assessment Reviewed 2026-09-20 by Gabor Kiss against published evidence. Two success stories carry real substance and both are anonymized: an entity-resolution model that reconciles a hotel distributor's 400,000-property master against more than 30 supplier feeds, which the write-up describes making those matching decisions unattended every day, and a cache and data-lake rebuild for a tourism company serving over 50,000 requests a minute under 200 milliseconds, with demand and supplier-price models keeping the cache warm. Both were published in September 2022 and nothing has followed them; the client wall carries 26 logos with no engagement description attached, and the private generative-AI assistant the site now leads with is a product page describing a RAG architecture, with no client running it named. What is checkable is the bench: 14 named people with LinkedIn and GitHub profiles, most of them data engineers and data scientists, a public GitHub org whose Airflow-Pentaho plugin was still maintained in late 2025, and a technical blog posting one to three pieces a month through September 2026. Best for travel and hospitality data platforms where the engineering track record matters more than a reference you can call. ### Key strengths - The cache and data-lake study publishes hard figures: 50,000-plus requests a minute under 200ms, 95% better cache efficiency and 45% fewer supplier calls, with two prediction models feeding the cache - The team page names 14 people with LinkedIn and GitHub links, most of them data engineers and data scientists rather than sales or delivery managers - Public engineering output is checkable: an Airflow-Pentaho plugin at 40 GitHub stars maintained into late 2025, and a Damavis entry in the Google Cloud partner directory ### Good to know - Every published case is anonymized and the newest dates to September 2022—ask for a speakable reference and a post-2023 engagement before shortlisting - The private generative-AI assistant is presented as a product page with a demo widget, not as a delivery—ask which clients run it and on whose infrastructure - The only address published is the registered office in Santa Margalida, Mallorca; if you need people in Madrid, confirm where the delivery team sits --- 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