Boom raises $12.7M to push AI deeper into hospitality operations
If you've ever waited hours for a door code or a basic answer, you've felt the gap between guest expectations and operator bandwidth. For teams running hundreds of units, those delays bleed into lost reviews, higher costs, and burned-out staff.
Boom, a Miami-based startup, just raised $12.7 million to scale an AI-powered property management system built to remove that drag. The goal: automate the repetitive, handle the dynamic, and free operators to focus on higher-value work.
Why operators should care
Guest expectations keep rising while staffing stays tight. AI isn't a nice-to-have anymore; it's a lever for response time, consistency, and margin control. If you're measured on turnaround, uptime, and NPS, this is where the gains live.
What Boom is building
Founded in 2023 by entrepreneur Shahar Goldboim, Boom is betting on agentic AI-systems that run workflows end to end, not just answer questions. Their platform automates operations and takes on context-heavy tasks in real time.
- Communicates with guests across channels, with context.
- Dispatches maintenance and coordinates vendors based on priority and availability.
- Manages schedules dynamically to reduce gaps and prevent lapses.
- Automates workflows so issues move from report to resolution without manual chasing.
According to the company, hospitality businesses in 20 countries already use the system. Operators cite convenience and competitiveness as key drivers.
Who's backing the bet
The round was led by Avenue Growth Partners, with participation from industry veterans including former Hilton International CEO Ian Carter, Goldman Properties CEO Scott Srebnick, and Siemplify co-founder Garry Fatakhov-prior backers who doubled down.
Goldboim brings nearly two decades across real estate, retail, and tech, including DesignedVR (luxury vacation rentals) and Relaxpro (multi-state retail). That operator DNA shows in how Boom frames the work: fewer moving parts, faster cycles, cleaner handoffs.
Signals from the field
"Our mission is to take the heavy lifting out of property management so operators can deliver better guest experiences and build stronger businesses," said Goldboim. He notes their agentic AI modules are already producing results and this raise will help scale impact-improving guest satisfaction, profitability, and work-life balance.
Brian Goldsmith, co-founder and partner at Avenue Growth Partners, added: "Boom is creating a genuinely new category with its AI-first approach to hospitality operations. The team has already proven their platform can deliver immediate value, and their vision for agentic AI takes that potential even further."
What this funding means for your operation
- Faster product iteration on automation modules that reduce ticket volume and lag.
- Stronger go-to-market and support as they scale internationally.
- Expanded hiring across engineering, data science, and customer success-more depth for deployments.
A human note behind the mission
Goldboim shared that Boom's roots trace to his brother Alon's "pain turned into purpose" after losing his wife Reut. That resolve shaped the company's focus on work that actually helps people-guests, operators, teams.
Practical checklist: evaluating AI for property ops
- Integration fit: PMS, OTA, smart locks, ticketing, phone/SMS, payment, and device data.
- Quality controls: accuracy benchmarks, fallbacks, and clear escalation paths to humans.
- Operational transparency: audit logs, conversation histories, action trails, and reporting.
- Security and compliance: PII handling, role-based access, data retention, and vendor posture.
- Service design: SLAs, onboarding timeline, change management, and support coverage hours.
- ROI plan: baseline current metrics (response time, first-contact resolution, labor hours, guest satisfaction), then pilot against a control group.
- Cost model: per-unit or per-ticket clarity, overage policies, and seasonality considerations.
For additional context on where the real gains show up in service operations, this overview is useful: Reimagining service operations with generative AI.
Suggested rollout plan
- Pick 1-2 properties with steady volume and clean data. Define three success metrics upfront.
- Start with the top five repeatable intents (check-in, Wi-Fi, parking, amenities, maintenance) and one internal workflow (cleaning/turnover).
- Map escalations: what triggers human intervention, who owns it, and expected response windows.
- Run a 30/60/90-day cadence: weekly QA on conversations, monthly metric reviews, and scope expansion only after thresholds are met.
- Document wins and misses; turn them into SOP updates and training for the next cohort of properties.
If your team is building AI fluency to support this kind of rollout, consider this resource: AI Automation Certification from Complete AI Training.
The takeaway
For guests: fewer hours waiting, more seamless stays. For operators: tighter cycles, cleaner handoffs, and maybe-finally-some time off.
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