Mews Acquires DataChat: AI Agents Move From Idea to Daily Operations
Published on: October 29, 2025
Mews has acquired DataChat, an AI company known for generative AI and natural language processing. For hotels and event venues, this means smarter systems that learn, adapt, and act across the entire operation without constant human intervention.
The vision: an AI-first operating system that handles revenue, service, and decisions in real time. Less manual work. Faster wins. Clearer numbers.
Why this matters for hotel and event leaders
Most PMS tools handle bookings and check-ins. Mews is pushing further-into autonomous agents that talk to your data, spot patterns, and trigger actions.
Think of a system that adjusts pricing, predicts arrivals, schedules staff, and personalizes offers, while your team focuses on guests and events.
What DataChat adds to the Mews ecosystem
DataChat brings conversational intelligence: ask questions in plain language, get instant answers, and trigger workflows. No SQL, no reports buried in email.
- Ask: "How did ADR trend by segment this week?" Get the chart and a short explanation.
- Ask: "If we shift BAR +5% for Fri-Sun, what's the forecasted pickup?" See the scenario before you approve it.
- Ask: "Where are we missing upsell revenue pre-arrival?" Get guest cohorts and suggested offers.
From PMS to AI-first operating system
Instead of static rules, autonomous agents act across reservations, distribution, housekeeping, F&B, and events. They learn from your data and keep tuning decisions as signals change.
- Revenue: Auto-adjusts rates by market demand, lead time, and channel mix.
- Labor: Predicts arrivals and departures to set staffing levels and task timing.
- Guest experience: Flags at-risk stays, triggers recovery offers, and routes tasks.
- Distribution: Rebalances inventory and parity without manual checks.
Day-to-day outcomes you can expect
- Fewer spreadsheets, fewer status meetings-decisions happen in-system.
- Faster response to spikes: events, weather, flight changes, local demand swings.
- More consistent service quality across shifts and properties.
- Managers spend time on strategy, not report wrangling.
How to prepare your property for agentic systems
- Clean data first: Standardize room types, rate codes, market segments, and source tags. Bad inputs limit results.
- Integrations: Connect PMS, RMS, CRS, POS, housekeeping, and guest messaging. Agents need full context.
- Guardrails: Set approval limits for pricing, comps, and overbooking. Define who approves what.
- Roles and training: Teach teams to ask better questions and review AI suggestions quickly.
- Pilot scope: Start with one property or cluster, one use case (e.g., weekend pricing), 6-8 weeks.
- Metrics: Agree on a small KPI set and lock it before you start.
Risks to plan for-and how to handle them
- Incorrect outputs: Keep human review on high-impact actions at launch, then reduce over time.
- Data privacy: Confirm data residency, access controls, and audit trails with your vendor.
- Bias in decisions: Monitor rate and upgrade decisions by segment to avoid unfair patterns.
- Change fatigue: Share quick wins weekly. Celebrate saved hours, recovered revenue, and guest feedback.
What success can look like in 90 days
- +2-5% ADR uplift on targeted dates with stable conversion.
- 10-20% fewer manual pricing overrides and parity fixes.
- 5-10% improvement in on-time room readiness and task completion.
- Faster service recovery with measurable lift in review scores on problem stays.
Where this is heading
Mews is moving from helpful software to systems that run parts of the hotel on their own-with clear approvals and visibility. DataChat's conversational layer makes that accessible to every manager, not just analysts.
For operators, the next edge is simple: better decisions, made faster, with less drag on your team.
Learn more and take action
Explore the Mews platform and its approach to AI agents here: Mews.
If you want structured training on AI skills for hospitality roles, browse curated options by job role: Complete AI Training - Courses by Job.
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