AI Consulting in Orlando

Large theme-park-adjacent hospitality businesses don't operate on a nine-to-five schedule, and the after-hours inquiry problem is where most operators leak the most revenue. A missed-call responder or web-intake bot doesn't replace a front-desk agent — it captures the lead, qualifies the request, and routes it to the right team with notes already logged before the first human picks it up in the morning. For multilingual properties, model-layer translation handles initial contact in the guest's preferred language without requiring dedicated staff per language. The build scope depends on what your current stack looks like — property management system, booking platform, and communication channels all affect integration complexity. A starting-point audit maps those data flows before any configuration begins, so the build fits the actual operation rather than a generic hospitality template.

ITAR and export control obligations mean the first question isn't 'what can AI do for us' — it's 'what data is in scope and where does it go.' Any workflow automation build for a defense contractor or simulation company starts with a data-flow mapping exercise: which workflows touch controlled technical data, which don't, and what the contractual obligations say about third-party processing. For workflows that involve no controlled technical data — internal scheduling, HR coordination, vendor procurement communications — standard cloud-based automation tooling is typically appropriate with proper BAA or DPA documentation. For workflows adjacent to technical data, we scope integrations that process within the organization's existing controlled environment or use self-hosted model endpoints that keep data inside the perimeter. The build documentation we produce includes the data-flow diagram and the model endpoint specifications, written to support the organization's ITAR compliance review before go-live.

HIPAA compliance for an AI integration comes down to three things: what data the build touches, how it's processed, and what the Business Associate Agreement covers. For patient-facing workflows — appointment scheduling, after-hours inquiry response, referral coordination — we route through model providers that offer signed BAAs and zero-retention data processing: Azure OpenAI, Anthropic's enterprise endpoint, or Google's Vertex AI healthcare configurations. The build itself uses read-only or narrowly scoped EHR API access rather than broad admin credentials, so the integration can only see the patient records or scheduling slots the workflow actually needs. For intake-side automation, the qualifying questions and response logic are reviewed against Florida's patient communication rules and the specific EHR platform's API terms before deployment. We don't ship patient-facing healthcare automation without the BAA executed and the data-flow documentation reviewed by the operator's compliance contact.

Florida's Division of Hotels and Restaurants under DBPR sets licensing and operational requirements that touch a few workflow areas. Automated booking and event-intake tools that collect payment data must comply with PCI DSS requirements independent of any AI layer — the automation sits on top of a compliant payment processor, not around it. For food-service operations, AI-assisted scheduling tools that interact with ServSafe certification tracking or health inspection documentation need to treat those records with the same access controls as any other compliance document. Florida also has a specific set of liquor license proximity and operational rules for event venues that should inform how an event-intake bot qualifies inquiries — a bot that books an event without surfacing the venue's license conditions creates a liability the operator didn't intend. These aren't showstoppers; they're scoping inputs. Golden Horizons builds these constraints into the intake logic at configuration time rather than discovering them after a build ships.

Most first builds ship in two to four weeks from signed scope to live deployment. The front end of that timeline is the audit — either the $99 AI readiness audit, which maps your current workflows, identifies the highest-leverage automation candidate, and quantifies the before-state so you have a baseline, or the $497 Founder Review Call for operators who want a prioritized roadmap across three to five workflows before committing to a build. After the audit, the build scope is fixed-price: one capability, defined deliverables, no hourly overages. For Orlando hospitality and healthcare operators, the most common first build is either a missed-call responder or an after-hours intake bot, both of which typically reach live status inside two weeks because they don't require deep EHR or property management system integration. Defense and simulation contractors take closer to four weeks because the data-flow review and compliance documentation add time up front — but that time prevents the kind of mid-build discovery that stretches a two-week project into three months.