Agentify your travel enterprise with a Decision Execution Layer
Travel is the hero vertical for the Decision Execution Layer. We sit between your Systems of Record PSS, CRS, NDC platforms, GDS, OTAs, loyalty, RMS, ancillary and disruption management systems and your agents, so every shop, price, booking, itinerary change and disruption-recovery decision carries context, governance, and memory.
Platform-agnostic approach ensures the best solution for your requirements.
Travel is full of agents in silos. We give them shared decision memory.
Pricing agents on the RMS. Shopping and booking bots on NDC and GDS. Concierge chat on the airline or OTA site. Disruption desks juggling irrops. Review triage scanning OTAs and Trustpilot. All making decisions without a shared Context Object no entities, no state, no record of which decisions worked. The Decision Execution Layer is the reasoning tier that sits between your PSS, CRS, NDC platforms, GDS, OTAs, loyalty, RMS, ancillary and disruption management systems and the vertical agents that act on top a Context Repo with data, governance and knowledge graphs that turns every booking, ancillary and recovery into feedback for the next decision.
Margin-aware pricing across RMS, NDC, GDS and OTAs
Shared Context Repo across PSS, CRS and loyalty
Hyper-personalised ancillaries with outcome tracking
Governed disruption recovery across OTAs and direct channels
Map, Build, Compound
Map
We map the travel stack PSS, CRS, NDC, GDS, OTAs, loyalty, RMS, ancillary and disruption management and the Systems of Knowledge (Notion, Slack, Confluence) around them. We pinpoint where decisions are made today, where Context Objects are missing, and where outcomes never flow back.
Build
We build the Decision Execution Layer the Context Repo, knowledge graphs and governance rules then wire vertical agents (revenue, ancillary, disruption recovery) and general agents on top. Every Context Object carries entities, state, decisions and outcomes.
Compound
Outcomes feed back. Pricing decisions inform next week's fares. Ancillary hits and misses tune timing. Disruption escalations sharpen governance. The Decision Moat deepens with every itinerary.
Why lemongrass.dev for travel
Travel is full of fragmented distribution, legacy PSS quirks and shallow AI pilots. You need a partner who treats the enterprise as an operating system and inserts the decision layer that makes agents informed, governed, and compounding.
We align with the metrics travel leaders actually track: RASK, yield, margin captured per booking, ancillary attach rate, churn risk on disruption, and brand health on OTAs and review sites.
We wrap your existing PSS, CRS, RMS, NDC, GDS, OTA, loyalty, ancillary and disruption management integrations SaaS stays, but gets re-bundled around agentic use cases.
Guardrails are baked into the execution layer, not bolted onto individual agents. Governance rules are first-class citizens inside the Context Repo.
Map, Build, Compound from decision-layer consulting through agent development, Context & Knowledge Graphs, and agent onboarding into live revenue, distribution and CX ops.
Pre-AI vs agentified travel
Shopping: flat fare lists on the brand website, NDC and GDS become prioritised, personalised flight and package recommendations drawn from Context Repo history.
Pricing: static, rule-based RMS fares become dynamic, margin-aware decisions that learn when discounts grow revenue and when they burn margin.
Booking: a simple PNR created in the PSS or CRS becomes a logged decision entity, state, decision, outcome feeding the next one.
Itinerary change and disruption: hardcoded policy in the PSS and disruption management tool becomes optimisation for customer lifetime value and churn risk.
CX: static responses become continuous improvement via outcome tracking across CX tools, OTAs and review sites low-impact issues handled in-brand, high-risk irrops escalated with full context.
The Decision Moat: every booking, ancillary, and disruption recovery becomes a compounding advantage competitors cannot replicate.
Near-term agentic use cases for travel
Margin-Aware Pricing
Pricing agents on top of the RMS reason over the Context Repo current demand, booking pace, channel mix, past outcomes and decide when to discount to win bookings versus when to hold fare to protect margin.
Fare decisions become dynamic and margin-aware across brand site, NDC, GDS and OTAs. Every call is logged so the next one is sharper.
Hyper-Personalised Ancillaries
Seat selection, extra bags, lounge passes, insurance, airport transfers, tour add-ons not only what to upsell but when. Agents read the Context Object across PSS, CRS and loyalty and trigger offers at the moment most likely to convert.
In-trip concierge agents, airport bots and upgrade prompts share one Context Repo. Hits and misses feed back into the decision memory.
Agentic Support
Traveller queries across website chat, WhatsApp, email and phone fare questions, itinerary changes, disruption updates, post-trip follow-ups handled by brand-consistent agents drawing on the Context Repo for bookings, preferences and loyalty history. Complex or top-tier elite issues escalate to a human with the full Context Object attached.
Every ticket becomes a logged decision what was asked, what was offered, what worked sharpening the next response.
CX Monitoring
Agents watch the full traveller journey PSS alerts, in-app chats, gate agent notes, in-flight surveys, post-trip feedback and flag friction early. Issues are routed to the right team before they become a negative review, with the full Context Object attached.
CX becomes a live signal on the operations floor, not a post-trip post-mortem.
Social Monitoring
Agents scan OTA reviews, Trustpilot, TripAdvisor, Skytrax and X around the clock. Sentiment, recurring themes and route- or product-level issues land in the Context Repo with the traveller, itinerary and booking linked in so recovery can start before the next review goes live.
Brand health moves from a monthly dashboard to a live, route- and product-level signal agents can act on.
AI-Led Operations
Crew, ground ops, turnaround and disruption desks run off a shared Context Repo. Agents sequence tasks based on departures, arrivals, elite flags and SLA risk humans approve edge cases, agents handle the rest. Every completed task feeds back into the next day's plan.
Daily operations stop being run from spreadsheets and shift handovers and start compounding.
Decision layers, proven in production
How airlines, OTAs and enterprise teams put the Decision Execution Layer between Systems of Record and their agent fleet and what compounded after.
Let’s map your Decision Execution Layer
Tell us which travel systems your agents touch PSS, CRS, NDC, GDS, OTAs, loyalty, RMS, ancillary or disruption management. We’ll map the decision points, design the layer, and start compounding.