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Why FareOS

Domain expertise. Modern architecture. AI built in.

The trifecta that legacy booking engines cannot replicate: 15+ years of GDS and NDC expertise, a 2024 Go microservices build, and a certified Anthropic Claude Code Partnership.

15+ yrs
GDS + NDC distribution expertise
2024
Architecture build year
22
Live flight supplier integrations
500+
Travel agencies on FareOS

The trifecta

What makes FareOS different

Three properties that take years to build and cannot be shortcut. Each one matters independently; all three together are what WNS calls a transformation partner.

01history_edu

15 years of GDS and NDC expertise

ecogo.ai has been building and operating travel distribution systems since 2009. That means deep knowledge of how GDS billing works, where NDC breaks, how airlines differ, and what breaks at 3 AM on a public holiday.

02architecture

Purpose-built in 2024 — not retrofitted

FareOS was architected from scratch in 2024 on Go microservices. No legacy monolith underneath. No .NET or PHP layer wrapped in an API facade. The architecture handles high concurrency, low latency search, and supplier isolation as first-class properties.

03smart_toy

Certified Anthropic Claude Code Partner

ecogo holds the Claude Partner Badge: Claude Code — issued by Anthropic. Certified to scope, deploy, configure, and run Claude Code activations end-to-end. eva, the AI layer in FareOS, is one product of that depth. The same capability extends to enterprise AI tooling deployments for travel clients.

Claude Partner Badge: Claude Code — issued by Anthropic

Verified credential

Claude Partner Badge: Claude Code

Issued by Anthropic · July 2026

Certifies that ecogo can scope, deploy, configure, and run Claude Code activations end-to-end for enterprise clients — configuration packs, security questionnaires, custom Skills and hooks.

Verify on Credlyopen_in_new

Architecture

How FareOS is built

Decisions made in 2024 that a legacy engine cannot retrofit without a full rewrite.

01bolt

Go microservices

The FareOS search and booking engine is written in Go. High concurrency, low memory footprint, predictable latency. Built to handle hundreds of simultaneous supplier queries without a distributed queue tax.

02hub

Supplier isolation by design

Each of the 22 supplier integrations runs as an isolated service. A failure at one supplier — timeout, API change, rate limit — does not cascade. Agents continue booking on the remaining suppliers without interruption.

03account_balance_wallet

Wallet-safe booking gate

FareOS enforces a wallet-safe gate at the payment layer: money only moves after the supplier confirms the seat. This is not a retry loop — it is a structural contract enforced by the booking engine.

04compare_arrows

Normalized wire format

Every supplier — GDS, NDC, LCC — returns results in the same FareOS wire format. One schema, all suppliers. This is what makes multi-source search, comparable fares, and per-supplier analytics possible.

05layers

Full post-booking lifecycle

FareOS is not a search tool with a booking form. Void, refund, reissue, seat amendment, schedule change, ancillary add — all covered, all supplier-specific logic handled inside FareOS rather than pushed to the agency.

06route

Standardized provider protocol

New suppliers follow the FareOS provider protocol — a standardized integration framework for auth, request/response normalization, capability flags, and error handling. New airlines go live in 2–4 weeks.

historyLegacy booking engine
  • .NET or PHP monolith
  • Single GDS connection
  • No NDC or LCC direct
  • Manual refunds
  • No AI layer
  • New supplier: months
rocket_launchFareOS
  • checkGo microservices
  • check22 suppliers (GDS + NDC + LCC)
  • checkWallet-safe booking gate
  • checkRefund Mitra automation
  • checkeva AI (Anthropic Claude)
  • checkNew supplier: 2–4 weeks
trending_upWhat your agency gets
  • arrow_forwardLower latency under load
  • arrow_forwardBest fare across all sources
  • arrow_forwardNo orphan PNRs
  • arrow_forwardLess manual ops work
  • arrow_forward3× booking capacity per agent
  • arrow_forwardGrowing supplier network automatically

Architecture questions

Frequently asked questions

Why Go instead of Node.js or Java for a booking engine?add

A booking engine makes tens of simultaneous outbound HTTP calls per user search — one per supplier. Go handles this with goroutines and channels: lightweight, no callback pyramid, predictable memory. A Node async chain or a thread-per-request Java model both show latency and memory issues at the search scale FareOS operates.

What does "AI-native" mean in practice for FareOS?add

AI-native means the AI layer (eva, powered by Anthropic Claude) is designed into the product workflow — not bolted on as a chatbot widget. eva has access to booking data, can take actions (summarize queue, flag anomalies, handle WhatsApp queries), and is grounded on the FareOS knowledge base. It is not a generic LLM answer box.

How is 15 years of experience relevant if the code was written in 2024?add

The expertise is in the design decisions: which supplier API quirks to handle gracefully, which edge cases in the GDS fare filing logic cause phantom charges, which NDC response schemas have undocumented breaking changes. That knowledge is encoded in the FareOS provider protocol and test suites — it cannot be rebuilt quickly.

Is FareOS available as an API for developers?add

Yes. FareOS exposes a booking API — OTAs and tech teams use it as the distribution backend. Book a demo and the team will walk you through the API surface, supplier coverage, and onboarding timeline.

See the architecture in action

A platform review shows the live system — multi-source search, booking flow, supplier isolation, and eva AI — with your specific supplier mix as the context.