```json { "title": "Best route optimization APIs for cold chain delivery", "url": "https://kardinal.ai/best-route-optimization-api-cold-chain-delivery/", "datePublished": "2026-09-18", "dateModified": "2026-09-25", "language": "en-GB", "description": "A comparison of the 11 best route optimization APIs for cold chain delivery, benchmarked against constraints representative of the market.", "author": "Kardinal", "publisher": "Kardinal" } ``` # Best route optimization APIs for cold chain delivery # Best route optimization APIs for cold chain delivery > **In short:** Among route optimization APIs for cold chain delivery, Kardinal dominates this sector ranking by a wide margin. Its only real gap concerns hourly cost by time of day, a niche need covered solely by Solvice. - **11** APIs compared in this sector - **98%** of cold chain constraints covered by Kardinal, ranked 1st - **80%** Solvice, the closest competitor - **Premium > 70%:** Kardinal (98%), Solvice (80%), LogisticsOS (79%), HERE (72%). - **Standard 50-70%:** Google (68%), NextBillion AI (65%), GraphHopper (51%). - **Basic < 50%:** Timefold (46%), Verso (42%), Routific (36%), Mapbox (29%). Fresh product delivery combines constraints that few other sectors stack to this degree: temperature-controlled compartments, multi-temperature zones within a single vehicle, expiry dates that dictate the order goods leave the depot, refrigeration-unit range that cannot be exceeded. An optimizer that ignores these constraints produces routes that break the cold chain, with direct regulatory and food-safety consequences. This article compares eleven route optimization APIs (Kardinal, Solvice, LogisticsOS, HERE, Google, NextBillion AI, GraphHopper, Timefold, Verso, Routific, Mapbox) on their ability to handle the specific constraints of cold chain delivery. > **A sector analysis, drawn from the full benchmark.** For a market-wide view across all solutions and all sectors: [the main guide to route optimization APIs](https://kardinal.ai/best-route-optimization-api/). The raw data sits in the [2026 benchmark](https://kardinal.ai/benchmark-route-optimization-api-2026/), and the price lists in the [pricing comparison](https://kardinal.ai/route-optimization-api-pricing-2026-comparison/). ## Key takeaways 1. In this sector, **Kardinal covers 98% of the relevant constraints**. Solvice follows (80%), then LogisticsOS (79%) and HERE (72%). 2. **Managing multi-temperature zones within a single vehicle**, useful for delivering frozen, chilled and ambient goods on the same route, is fully covered only by Kardinal. 3. Kardinal has only **one real gap** in this sector: hourly cost by time of day, a very niche need, covered solely by Solvice. 4. **Lexicographic optimization**, which ranks objectives rather than weighting them, is only available from Kardinal and HERE. The others fall back on a weight for every criterion, which quickly turns into a sprawling setup to fine-tune. Ranking keeps multi-objective optimization simple and readable. ## What makes cold chain delivery genuinely complex ### Temperature-controlled compartments A single vehicle can carry frozen (-18°C), chilled (0-4°C) and ambient goods at the same time, in separate compartments whose capacity has to be respected independently. The optimizer has to assign each order to the right compartment, not just check the vehicle's overall capacity. ### Dispatch order driven by expiry dates Products closest to their expiry date generally have to leave the depot first and be delivered as a priority, a logic close to FEFO (first expired, first out) applied to the route itself. An optimizer that ignores this constraint can produce a route that is optimal on distance and unworkable in practice. ### Refrigeration unit range A refrigeration unit runs on limited range before it needs recharging or a return to the depot. A route that runs too long exposes goods to a cold-chain breach toward the end of the trip. ### Strict receiving windows in grocery retail As with standard retail, grocery chains impose precise receiving windows, with one extra twist: a late arrival can mean a product turned away at the dock for a temperature non-compliance rather than a simple reschedule. ### Traceability and breach alerts Beyond planning, some operators want to be able to flag and document a cold-chain breach mid-route, for regulatory and product-traceability reasons. ## The critical constraints for a cold chain delivery API Three levels of requirement structure the market: the classic baseline everyone covers, the intermediate constraints that are indispensable in practice, and the advanced constraints that genuinely make the difference on cold chain. **Classic (3)** - **Strict time windows** — Covered everywhere, with varying levels of granularity. Covered by: every vendor. - **Capacity per temperature compartment** — Respecting the capacity of each zone (frozen, chilled, ambient) independently. Covered by: every vendor except Mapbox. - **Delivery from a refrigerated depot** — The core movement of the business. Covered by: every vendor. **Intermediate (4)** - **Refrigerated vehicle profile** — Travel times and access constraints specific to refrigerated vehicles. Covered by: Kardinal, Solvice, LogisticsOS, HERE and NextBillion AI. Partial at Google and GraphHopper. - **Dispatch priority by expiry date** — Sending out the products closest to their expiry date first. Covered by: Kardinal, Solvice, LogisticsOS and HERE. Absent at GraphHopper, Mapbox, Routific, Timefold and Verso. - **Refrigeration unit range** — Capping route duration to the cold unit's range. Covered by: Kardinal, Solvice, LogisticsOS, Google and NextBillion AI. Absent at GraphHopper, Mapbox, Routific, Timefold and Verso. - **Predictive traffic** — Expected traffic is factored in before optimization, not corrected afterwards. Covered by: Kardinal, Solvice, GraphHopper, Google, HERE, Mapbox and NextBillion AI. Absent at Routific, Timefold and Verso. **Advanced (5)** - **Multi-temperature zones in a single vehicle** — Assigning each order to the right compartment (frozen, chilled, ambient) on the same route. Covered by: Kardinal only. Partial at Solvice and LogisticsOS. - **Lexicographic optimization** — First meeting receiving windows, then minimizing costs, with no weights to calibrate between the two. Covered by: Kardinal and HERE only. - **Cold-chain breach alert and traceability** — Flagging and documenting a temperature threshold breach mid-route. Covered by: Kardinal and LogisticsOS only. - **Route compactness** — Keeping each route geographically tight to limit time outside controlled temperature. Covered by: Kardinal, Solvice and LogisticsOS only. - **Time-of-day-dependent hourly cost** — Modelling a premium on defined slots. A niche need, rare in the sector's rate structures. Covered by: Solvice only. ## The cold chain delivery APIs compared ### Kardinal — the most complete API for the cold chain (98% coverage · 1st/11) Kardinal is the most complete solution for fresh product delivery. It is the only vendor to fully cover multi-temperature zones within a single vehicle, a key point for delivering frozen, chilled and ambient goods on the same route, and it also combines lexicographic optimization, route compactness and cold-chain breach alerting. Its only real gap in this sector: hourly cost by time of day, a very niche need, covered solely by Solvice. **Ideal for:** Cold chain operators of every size, from regional multi-temperature routes to large grocery distribution networks with traceability requirements. ### Solvice — the closest challenger (80% coverage · 2nd/11) Solvice takes second place, carried by solid coverage across almost every family: refrigerated vehicle profile, dispatch priority by expiry date, refrigeration unit range. It partially covers multi-temperature zones. Its limit: no lexicographic optimization. With a model that rich, balancing several objectives means setting a weight on each criterion, and the configuration quickly becomes a heavy machine to fine-tune. **Ideal for:** Operators whose costs genuinely vary with the time of day (night premiums, peak-hour pay), a rare case, and who have the resources to tune weights criterion by criterion. ### LogisticsOS — traceability and cost trade-offs (79% coverage · 3rd/11) LogisticsOS stands out for its coverage of cold-chain breach alerting and traceability, alongside Kardinal only. It also covers the refrigerated vehicle profile, dispatch priority and refrigeration unit range well. **Ideal for:** Operators with a strong regulatory requirement for documenting and tracing temperature breaches. ### HERE — strict priority ranking (72% coverage · 4th/11) HERE is the only solution besides Kardinal to offer lexicographic optimization, and covers the refrigerated vehicle profile and dispatch priority by expiry date well. Its limit: no refrigeration-unit-range constraint, no route compactness. **Ideal for:** Operators who want to rank their priorities strictly and already run the HERE mapping ecosystem. ### Google — strong mapping, advanced constraints absent (68% coverage · 5th/11) Google covers refrigeration unit range and predictive traffic well, but none of the sector's advanced constraints are covered, even partially. **Ideal for:** Operators with standard cold-chain needs, with no multi-temperature or advanced traceability requirements. ### NextBillion AI — solid on the fundamentals, behind on advanced (65% coverage · 6th/11) NextBillion AI covers the refrigerated vehicle profile, refrigeration unit range and predictive traffic well, but none of the sector's advanced constraints are covered. **Ideal for:** High-volume operators with standard refrigerated delivery needs. ### GraphHopper, Timefold, Verso, Routific and Mapbox — insufficient coverage for professional cold chain (51% → 29%) - **GraphHopper (51%)** covers predictive traffic and partially the refrigerated vehicle profile, but no dispatch priority by expiry date and no refrigeration unit range. - **Timefold (46%)** and **Verso (42%)** lag on most of the sector's fundamentals. - **Routific (36%)** and **Mapbox (29%)** are not designed for professional cold chain operations. ## Summary table | Solution | Coverage | Multi-temperature | Refrigeration unit range | Breach traceability | Lexicographic | |---|---|---|---|---|---| | Kardinal | 98% | Full | Full | Full | Full | | Solvice | 80% | Partial | Full | No | No | | LogisticsOS | 79% | Partial | Full | Full | No | | HERE | 72% | No | No | No | Full | | Google | 68% | No | Full | No | No | | NextBillion AI | 65% | No | Full | No | No | | GraphHopper | 51% | No | No | No | No | | Timefold | 46% | No | No | No | No | | Verso | 42% | No | No | No | No | | Routific | 36% | No | No | No | No | | Mapbox | 29% | No | No | No | No | ## Our verdict Fleet size is not what should drive the choice. What matters is how much of your operation goes beyond the classic constraints. Start from the four leading solutions on cold chain, then narrow the list according to your needs. **Starting point · the top 4** Kardinal, Solvice, LogisticsOS and HERE all cover the fundamentals of cold chain delivery well. Kardinal leads the group by 18 points. **You deliver frozen, chilled and ambient on the same route** HERE, which does not cover multi-temperature zones, drops out. Kardinal, Solvice and LogisticsOS remain. **You need to trace temperature breaches** Solvice, which does not cover this constraint, drops out in turn. Kardinal and LogisticsOS remain, and only Kardinal fully covers multi-temperature zones and ranks its objectives without a stack of weights. **And on price** Among the top 4, Kardinal is also the most competitive overall, including for mid-size fleets. The details are in our [2026 pricing comparison](https://kardinal.ai/route-optimization-api-pricing-2026-comparison/). ## Delivering fresh products with multi-temperature or traceability requirements? Test Kardinal optimization on your own data, with no commitment. **[Start with the free tier →](https://console.kardinal.ai/)** · **[Read the documentation](https://developers.kardinal.ai/)** · **[See the full benchmark](https://kardinal.ai/benchmark-route-optimization-api-2026/)** ## FAQ ### Which route optimization API should you choose for cold chain delivery? Kardinal is the most complete solution, with 98% sector coverage, and the most competitive on price among the top 4. Solvice (80%) and LogisticsOS (79%) follow, ahead of HERE (72%). If you deliver frozen, chilled and ambient goods on the same route, the shortlist narrows to Kardinal, Solvice and LogisticsOS; with traceability requirements on top, to Kardinal and LogisticsOS. ### How do you manage several temperature zones in a single vehicle? A vehicle can carry frozen, chilled and ambient goods at the same time in separate compartments, each with its own capacity to respect. Kardinal is the only solution in the panel to fully cover this constraint; Solvice and LogisticsOS cover it only partially. ### How do you prioritize deliveries by product expiry date? This constraint sends the products closest to their expiry date out of the depot first, a logic close to FEFO applied to the route. Kardinal, Solvice, LogisticsOS and HERE offer this capability. ### Can a route optimization API document a cold chain breach? Yes, but only two solutions offer it today: Kardinal and LogisticsOS. This capability flags and documents a temperature threshold breach mid-route, to meet regulatory and product-traceability requirements. ### How does refrigeration unit range affect route planning? A refrigeration unit runs on limited range before it needs recharging. The optimizer has to cap route duration to that range to avoid a cold-chain breach toward the end of the trip. Kardinal, Solvice, LogisticsOS, Google and NextBillion AI cover this constraint. ## Going further - [Retail & distribution](https://kardinal.ai/best-route-optimization-api-retail-distribution/) — Receiving windows, tiered subcontracting and multi-depot rotations: the constraints that separate the APIs in distribution. - [Parcel delivery](https://kardinal.ai/best-route-optimization-api-parcel-delivery/) — Stop density, strict time windows and daily disruptions: the constraints that separate the APIs on the last mile. - [Long-haul / FTL](https://kardinal.ai/best-route-optimization-api-long-haul-transport/) — Regulation, driving hours and rate modeling on full truckload.