Reduce downstream latency
Insulate Yalago from slow PULL suppliers using intelligent acceleration and adaptive freshness — not blunt caching.
Helping Yalago improve supplier response times, increase search completion within the 3-second SLA, reduce infrastructure costs and build a future-ready hotel distribution platform.
Internally managed inventory and PUSH suppliers respond in under 40 milliseconds. Based on the information shared, the primary opportunity for further optimisation lies in downstream PULL supplier integrations, where higher response times become the main constraint on end-to-end search performance. When supplier latency exceeds the target 3-second SLA, searches may be completed without all available options, impacting search completeness, increasing infrastructure load, and limiting the platform's ability to consistently deliver the best available inventory.
Peak query volume across the distribution platform.
Hard ceiling after which results are terminated.
Share of requests lost or downgraded at peak.
Cognirock proposes a Supplier Performance & Intelligent Acceleration Program designed to optimise supplier performance, improve search completion and prepare the platform for future growth.
Analyse the current platform performance to identify the main bottlenecks, evaluate PULL supplier behaviour and define a data-driven optimisation roadmap.
Design and implement a Proof of Concept to validate, in a real environment, the improvements identified during the diagnosis and demonstrate their impact before a full rollout.
Build and deploy the solution validated during the PoC into production, integrating it with Yalago's architecture and ensuring a controlled transition.
For the 6 months following go-live, we run continuous follow-up to measure performance, optimise operation and support Yalago's team through adoption. At the end of the period, Yalago can opt into an ongoing support and evolution service covering maintenance, new features and continuous optimisation.
A platform capable of serving more searches within the SLA, reducing supplier API traffic and infrastructure costs, improving resilience, and ultimately increasing booking conversion while supporting Yalago's continued global growth.
Every search fans out to contracted inventory, PUSH and PULL suppliers in parallel. PUSH and contracted responses are fast; PULL suppliers introduce highly variable latency and frequent timeouts.
< 40 ms · deterministic latency · in-house indexes.
Variable latency · timeouts · throttling at peak.
Searches terminated at 3 s → incomplete results → lost upside.
Insulate Yalago from slow PULL suppliers using intelligent acceleration and adaptive freshness — not blunt caching.
Serve frequently requested inventory from an acceleration layer while preserving real-time accuracy.
Lower the number of outbound API calls during peaks — directly addressing throttling and rejection rates.
Decouple search growth from supplier traffic growth and from raw infrastructure scaling.
Each phase is independently valuable and builds on the previous one. Below is the expected timeline from kick-off to the end of the follow-up period.
Analyse the current platform performance to identify the main bottlenecks, evaluate PULL supplier behaviour and define a data-driven optimisation roadmap.
Design and implement a Proof of Concept to validate, in a real environment, the improvements identified during the diagnosis and demonstrate their impact before a full rollout.
Build and deploy the solution validated during the PoC into production, integrating it with Yalago's architecture and ensuring a controlled transition.
Continuous follow-up during the 6 months after go-live to measure performance, optimise operation and support Yalago's team through adoption. Optional ongoing support and evolution service afterwards.
Instead of one cache lifetime for everything, refresh decisions are derived continuously from product, market and supplier signals — keeping accuracy high and supplier traffic low.
Continuous monitoring of response times, error rates, availability consistency, supplier health and refresh efficiency — feeding the acceleration layer in real time.
| Supplier | Avg RT | Health | Hit ratio |
|---|---|---|---|
Supplier Alpha | 38 ms | 98 | 92% |
Supplier Bravo | 220 ms | 86 | 71% |
DMC Cobalt | 1,840 ms | 64 | 38% |
DMC Sierra | 2,640 ms | 41 | 22% |
Supplier Quartz | 95 ms | 94 | 88% |
Specialist Onyx | 2,980 ms | 32 | 14% |
Hotel distribution, connectivity, API optimisation and marketplace technology — built specifically for this industry, not retrofitted from generic infra.
We design systems for the constraints that matter at Yalago's scale — latency tails, supplier behaviour and operational headroom.
Bundleport already operates as a hotel connectivity marketplace — the same foundation powers the supplier intelligence and acceleration layer.
A dedicated team of 3–4 engineers running the full program end-to-end — from diagnosis to production rollout and 6 months of follow-up.
Invoicing is split into three milestones aligned with the delivery of each stage of the program.
From reducing latency today to creating the most intelligent hotel supplier acceleration layer in the industry.