AI Revenue Management System
LodgIQ
SF 8.5AI revenue management for hotel teams
Contact sales
AI Revenue Management System
Pace
SF 8.0Legacy automated revenue platform for hotels
Contact sales
Quick decision guide
Choose based on your workflow
LodgIQ may fit better if...
- AI Pricing
- Group Pricing
- Forecast Tools
Pace may fit better if...
- Automated Pricing
- Revenue Forecasts
- Pickup Monitoring
Overview
How each tool is described
LodgIQ
What is LodgIQ?
LodgIQ is an AI-powered hotel revenue management and commercial strategy platform that combines dynamic pricing, demand forecasting, market intelligence, business analytics, group pricing, and conversational AI for hotel commercial teams.
- Revenue optimization: LodgIQ uses machine learning to forecast demand and willingness to pay, then recommends rates and controls at room-type, rate-code, length-of-stay, and segment levels. Its models combine hotel performance and booking data with signals such as competitor rates, market trends, events, flight activity, and weather.
- Automation and AI: revenue teams can operate LodgIQ in manual, co-pilot, or auto-pilot mode, allowing recommendations to remain advisory or automatically update rates and restrictions. LodgIQ also now includes AI Wizard, a conversational revenue-intelligence interface that combines predictive, generative, and agentic AI so users can question hotel data and surface commercial insights in natural language.
- Commercial intelligence: MarketIQ provides market, neighborhood, segment, and competitive intelligence; BusinessIQ analyzes hotel performance and reporting; ForecastIQ produces daily aggregate and segment-level forecasts; and GroupIQ evaluates group opportunities using incremental revenue, displacement, ancillary revenue, alternate dates, and optimized pricing.
- Commercial considerations: LodgIQ’s current public comparison lists Base at $6 per room for its Standard RMS, Pro at $8 per room with Advanced RMS and mobile capabilities, and Premium at $10 per room with Advanced RMS, mobile, and expanded business intelligence. Feature depth increases across areas such as mobile analytics, granular pace reporting, pickup analytics, and portfolio reporting.
LodgIQ is most relevant to independent hotels, management companies, and hotel groups that want automated pricing and restrictions connected to forecasting, market intelligence, group-sales decisions, business analytics, and conversational revenue intelligence rather than using a rate-recommendation tool in isolation.
Pace
What is Pace?
Pace Revenue was acquired by FLYR in September 2022 and its hotel revenue-management technology now operates as FLYR Hospitality. The current platform is an AI-first revenue strategy system for hotels and accommodation businesses, organized around Optimize, Insights, Planning, and Groups.
- Revenue optimization: Optimize generates hourly pricing and inventory-restriction recommendations using demand forecasting and price-sensitivity models. Hotels can run recommendations manually or automate their application, while revenue managers influence the AI through strategic directions rather than maintaining large sets of fixed business rules.
- Commercial intelligence: Insights centralizes PMS, rate-shopper, benchmarking, and other commercial data with transactional-level analysis, customizable dashboards, scheduled reports, custom metrics, and natural-language AI queries. It is designed to give revenue and commercial teams a common data layer for investigating performance measures such as pickup, occupancy, ADR, and RevPAR.
- Planning and group business: Planning supports rolling and locked forecasts, AI-generated baseline forecasts, versioning, forecast-accuracy tracking, scenario comparisons across periods and budgets, and structured approval workflows. Groups extends optimization to transient, corporate, and group demand with real-time displacement analysis, inventory allocation, rate recommendations, pickup and wash tracking, and forecast impact before a group is accepted.
- Integration ecosystem: FLYR Hospitality currently lists 26 integrations across PMS, CRS, intelligence, and marketing systems. Featured connections include Mews, Oracle OPERA Cloud, Cloudbeds, Apaleo, Stayntouch, CoStar STR, Amadeus Demand360, and RateGain, allowing its pricing, forecasting, and analytics workflows to use data from the hotel’s existing commercial technology stack.
FLYR Hospitality is most relevant to hotels and multi-property groups that want revenue optimization, business intelligence, forecasting, and group-business decisions operating from the same data and AI platform rather than separate RMS, BI, and spreadsheet workflows.
Side-by-side
Key differences
Criteria
AI Revenue Management SystemLodgIQ
AI Revenue Management SystemPace
Best for
AI Revenue Management System
AI Revenue Management System
Score
8.5/10
8.0/10
Pricing
Contact sales
Contact sales
Category / audience
AI Hotel Management & Operations Software › AI Revenue Management System
- hotel revenue management
- AI pricing
- machine learning RMS
AI Hotel Management & Operations Software › AI Revenue Management System
- dynamic pricing
- hotel revenue management
- automated pricing
Feature check
Side-by-side feature check
Feature
LodgIQ
Pace
AI PricingRecommends rates using demand and pickup
-
Group PricingModels group impact on hotel profitability
-
Forecast ToolsPredicts demand for commercial planning clearly
-
Market SignalsTracks competitor and demand changes clearly
-
Portfolio ViewsSupports multi-property revenue team oversight
-
Mobile AccessGives managers pricing views on mobile
-
12 capabilities compared.12 differentiating rows are shown first.
Use cases
Who they're built for
LodgIQ
- Optimize hotel room pricing decisionsUse AI recommendations for daily revenue decisions for hotel teams
- Evaluate group business profitability for hotelsCompare displacement and profit before accepting groups for hotel teams
- Track demand across market periodsMonitor pickup and demand changes across key dates
Pace
- Automate independent hotel revenue pricingReduce manual pricing work for smaller revenue teams
- Compare legacy Pace with FLYRUnderstand older Pace positioning before current FLYR evaluation
- Review pickup and demand trendsTrack booking pace changes before rate decisions for hotel teams
The trade-offs
Pros & cons of each tool
Trade-offs
LodgIQ
Pros
- Strong machine learning focus for revenue teams
- Group pricing tools add commercial decision depth
- Good fit for mid-market hotel portfolios
Cons
- Pricing requires direct vendor conversation and scoping
- Very small hotels may find it heavy
- Model quality depends on clean hotel data
Trade-offs
Pace
Pros
- Clear automation story for lean hotel teams
- Useful history for FLYR Hospitality comparisons clearly
- Pricing guidance can reduce manual spreadsheet work
Cons
- Standalone product status needs careful vendor confirmation
- Current packaging appears folded into FLYR Hospitality
- Less suitable than active current FLYR listing
Final verdict
Best fit depends on your workflow
Current catalog data shows meaningful overlap between LodgIQ and Pace. Use the signals below to decide based on workflow, ecosystem, pricing, and implementation fit.
Differentiators available
LodgIQ has 4 visible decision signals and Pace has 4.
Score signal
LodgIQ has the higher SoftFinders Score in the current catalog data.
Choose LodgIQ if…
- Optimize hotel room pricing decisions
- Evaluate group business profitability for hotels
- Track demand across market periods
- AI Pricing
Choose Pace if…
- Automate independent hotel revenue pricing
- Compare legacy Pace with FLYR
- Review pickup and demand trends
- Automated Pricing
TRY THEM YOURSELF
See which one fits your workflow
Both tools have their strengths, the best way to decide is to spend a few minutes inside each.