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Infinum Inc.

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infinum.comKarlovac, Croatia

Global, end-to-end software product development partner delivering digital products across the full lifecycle.

Overview

Infinum is a global, end-to-end software product development partner that helps organizations turn ideas into digital products. It covers the full digital solution lifecycle—from brand experience and product strategy to design and development—along with AI and data engineering, custom IoT solutions, enterprise platforms, and cybersecurity. With two decades of experience and a collaborative approach, Infinum partners with iconic brands and enterprises to deliver usable, scalable digital products and outcomes across web and mobile platforms.

Mission statement

To help organizations turn ideas into successful digital products through end-to-end strategy, design, development, and security.

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What we offer

Edmond Revenue Management System

Maximizes revenue for hospitality through advanced AI-powered insights and automation.

infinum.com/work/edmond-revenue-management-system/

Market segments

Market size by segment

Growth potential (CAGR)

Revenue management and dynamic pricing for hospitality

1.5 Billion USD12% CAGR

ML-driven capabilities that forecast demand, optimize room pricing, and automate rate adjustments to maximize RevPAR across a hotel portfolio.

Channel management

2.3 Billion USD11.5% CAGR

Capabilities to govern channel pricing, partner claims, inventory visibility, co-op/MDF allocation, and payments across distribution partners.

Group sales and corporate bookings

4 Billion USD15% CAGR

Automated quoting, collaboration, and AI-driven group pricing workflows that accelerate response times and maximize revenue from group bookings.

Application and product engineering

1297.71 Billion USD6.8% CAGR

End-to-end product and application engineering including custom software, SaaS, enterprise apps, IoT, MVPs, and commerce platforms to accelerate product-led growth.

More information about our offering

Edmond Revenue Management System

Edmond is a machine-learning driven revenue optimization system for hospitality. It ingests multiple internal and external data sources to predict occupancy, optimize room pricing, and synchronize availability across sales channels in real time.

  • Streamlines Management
    Enables easy access to critical revenue data for informed decision-making.
  • Enhances Data Accuracy
    Combines various data points for comprehensive insights and strategy development.
  • Informs Pricing Strategy
    Utilizes machine-learning algorithms to optimize rates based on demand forecasts.
  • Maximizes Booking Potential
    Ensures that rates are competitive and reflect market dynamics across all platforms.
  • Enhances Decision Making
    Empowers managers to make more informed choices with confidence based on machine-learning insights.
  • Stays Competitive
    Offers insights to adjust rates based on market trends and competition.
  • Improves User Experience
    Maximizes efficiency and minimizes training time for new users.
  • Simplifies Proposal Creation
    Automatically generates professional quotes, saving time for sales teams.

References

Methodology and sourcing behind the market figures shown above.

Revenue management and dynamic pricing for hospitality

Provided search results (IDeaS, EHL, RoomPriceGenie, Cvent, etc.) describe broad and growing adoption of AI-driven dynamic pricing and RMS in hospitality but do not include explicit market-size figures. Using that evidence of widespread deployment and industry commentary plus internal industry context (global hotel technology/RMS software plus related services), I estimate the current market for revenue management and dynamic pricing in hospitality at roughly $1.5 billion (software + services annually). Growth potential is driven by increasing AI adoption, higher RevPAR focus, and RMS penetration into independent and group hotels; I estimate a realistic CAGR of ~12% over the coming years (typical range for vertical SaaS/AI adoption in hospitality). No explicit market-size or CAGR figures were present in the supplied search results, so this estimate relies on the search results’ qualitative signals and general industry growth benchmarks.

Channel management

Estimated current market size (~2024) based on independent market reports: GrowthMarketReports (USD 2.14B in 2024) and Market Research Intellect / OpenPR (USD 2.5B in 2024). Forecasts from those reports (USD 6.4–6.97B by early-2030s) imply mid‑single‑digit to mid‑teens CAGRs; I selected a conservative midpoint (~11.5%) between reported CAGRs (10.9% and 13.8%) while noting lower and higher sector-adjacent growth figures in related through-channel/omni-channel reports.

Group sales and corporate bookings

No explicit monetary market size for "group sales and corporate bookings" automation was found in the provided results. I estimated size by treating this segment as the software/services portion of global group business travel. Using an internal benchmark (global business travel spend ≈ $1.2–1.4T pre-pandemic) and assuming group travel represents ~10–20% of that spend, group travel gross spend is roughly $130–280B. Software, automation, dynamic-pricing and services addressing group sales typically capture a small transaction/fee share (about 1–3% of gross group spend), implying an addressable market roughly $1.3–8B; the midpoint is about $4B. Growth (CAGR ≈15%) reflects accelerating adoption of AI-driven pricing, dynamic quoting, and automation as described in the sources, plus recovery and digitization trends in corporate meetings/events.

Application and product engineering

Estimated by mapping the requested segment to the broader global Product Engineering Services market. Primary source: MarketsandMarkets (2025) provides a recent, explicit valuation and forecast used for the estimate. Alternate published figures in the search results vary significantly (MarketResearchFuture: USD 198.02B in 2024, CAGR 10.16%; Grand View Research via Baker Tilly: USD 4,419.59B in 2024, CAGR 5.7%), so the MarketsandMarkets 2025 valuation and 2025–2030 CAGR (6.8%) were used as the principal basis while noting cross-report variance.

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