Agentic AI for travel, built for the moments that matter

Hallucination risk is the single most common concern we hear from travel ops leaders — and it's the right one. Three controls, applied together, eliminate it in our deployments:

• Grounded retrieval, not generative guessing. Every fare, fee, and policy answer is pulled live from your fare engine, GDS routing rates, or rate-loaded knowledge base – the AI does not invent numbers.
• Closed-set responses for pricing. When a traveler asks, "How much is a change fee for IROPs (Irregular Operations) on this PNR?", the AI quotes from the live rule, not from training data.
• Confidence thresholds + escalation. If the AI is below threshold on any policy or rate question, it either confirms with the traveler or escalates with full context – it never fills the gap with a plausible-sounding answer.

This is one of the seven lessons we documented across our 43 Evly deployments. The full breakdown of guardrails – and how to apply them – is in our AI in Customer Service handbook.

Yes, and it's enforced at every layer of the stack, not just the front end.

• Tokenization at ingestion. Card numbers and sensitive PII are tokenized before they ever touch agent or AI surfaces.
• Secure API integrations. All connections to your GDS, PSS, payment provider, and CRM are encrypted and protected by role-based access controls. The AI sees only what it needs to resolve the case — nothing more.
• PCI DSS Level 1, GDPR, ISO 27001. The three compliance pillars are continuously audited, not point-in-time stamps.

For the full security commitment, including how we handle chargebacks on disputed travel transactions, read our security & safety overview.

Brand voice is configured, monitored, and corrected continuously — not set once and forgotten.

• SOPs (Standard Operating Procedures) as the foundation. The AI is trained on your SOPs, fare rules, IROP playbooks, and loyalty policies – not a generic travel template.
• Brand guardrails. Tone, vocabulary, prohibited phrases, signature lines, and apology depth are all explicitly defined and enforced at generation time.
• Cultural adaptation. For brands operating across markets, the AI adapts register and formality to the traveler's locale – not just the language. (More on why this matters: global cultural standards and personalization.)
• Human-in-the-loop QA. A continuous sample of AI conversations is reviewed against brand-voice rubrics; corrections feed back into the model weekly.

This is exactly the hospitality peak season playbook we've refined across hotel groups, OTAs, and carriers.

Frustration is detected, not waited for. Three mechanisms work together:

• Real-Time Sentiment Analysis. Every message is scored on emotion, urgency, and intent. A drop below the configured threshold triggers immediate handoff – before the traveler asks for a human.
• Trigger phrases & escalation rules. Specific phrases ("I want to cancel everything", "I'm going to dispute this", "this is unacceptable") route directly to a senior agent, not the next-available queue.
• HITL (Human-In-The-Loop) handoff with full context. When the agent picks up, they see the full transcript, sentiment timeline, PNR, tier, and AI confidence summary. The traveler doesn't repeat anything.

This is the core of our human + AI model, and it's why our CSAT stays above 83% even during IROPs.

EverHelp is PCI DSS Level 1 and GDPR compliant, and ISO 27001 certified. Concretely, that means:

• Card data is tokenized – full numbers are never stored or displayed to AI or human agents
• All session recording and screen-sharing run over encrypted protocols
• Role-based access ensures every agent and every AI workflow sees only the minimum data needed to resolve the case
• Annual third-party audits across all three frameworks; quarterly internal reviews
• Documented retention policies aligned to your jurisdiction and your legal team's requirements

For the operational implications — including how PCI compliance reduces refund friction and protects SLAs on disputed transactions — see the linked guides.

This question gets at the fear most travel CX leaders carry: fragmented CX – where the experience falls apart between web chat, the call center, and social DMs.

EverHelp's agentic AI runs on a single conversation graph across:

• Voice (call center, IVR replacement)
• Live chat (your site, OBE checkout, app)
• Email
• WhatsApp, Telegram, Facebook Messenger, iMessage, SMS
• Social (X/Twitter, Instagram DMs, Facebook)

The same conversation context – PNR, tier, sentiment, intent – moves with the traveler when they switch channels. No re-explaining.

On language quality:

• 95+ languages supported natively, with parity SLAs across major markets
• Cultural-nuance detection adapts tone, formality, and apology depth to the traveler's locale, not just their language
• Continuous evaluation against native-speaker QA across the top 30 markets
• Local idiom handling – "delayed" in a US context vs. a Japanese context lands very differently; the AI handles both

The result: one CX, one brand voice, one service quality bar – across every channel and every market you operate in.