Qogita is a leading global wholesale B2B platform that is trying to revolutionize how products are discovered and procured. On a mission to simplify B2B trade, Qogita helps its customers generate higher margins and turnover while saving time with the help of its innovative technology.

By partnering with Meilisearch, Qogita is able to ensure high exposure for sellers and increased relevancy for buyers, resulting in an excellent buyer-seller interaction experience.

"Meilisearch has empowered us to deliver lightning-fast and highly relevant search results tailored to our customers' needs. Its seamless integration with our systems has positively impacted developer experience, making local environment setup, testing, and CI/CD automation significantly more efficient. Additionally, Meilisearch has proven to be a cost-effective solution, resulting in substantial savings for Qogita."
- Ivo Silva, Engineering Director at Qogita


The wholesale industry of today, due to its size and maturity, remains highly traditional in terms of business practices and procurement methods. This means suppliers are hard to find, hard to work with, and often resistant to even taking on new customers.

Qogita aims to address this challenge by making it incredibly easy for sellers and buyers to connect through its platform, all in one place. By offering innovative solutions such as AI-powered pricing and cost optimization, tailoring product search capabilities to users’ actual needs, and providing an excellent buyer-seller interaction via search.

Why Qogita chose Meilisearch

Prior to Meilisearch, Qogita used Algolia as their search provider and was satisfied in terms of functionality and performance. However, Qogita's team strove for further optimization when it came to both technology and costs. An evaluation was launched to assess alternatives, and a thorough comparison between Meilisearch, Typesense, and Algolia was performed.

The evaluation primarily focused on relevancy, ensuring that the search results were not significantly disrupted with Algolia's results serving as the baseline for comparison. Key searches were conducted for popular products and categories to determine the sorting order and overall performance. Additionally, the evaluation considered the handling of typos and common misspellings, which frequently occur in user searches.

The other factors that contributed to the choice included:

  1. Cost-effectiveness
    All the alternatives performed well in the key areas of evaluation, but Meilisearch emerged as the preferred choice due to its cost-effectiveness. Since Qogita has a relatively lean DevOps team, selecting Meilisearch Cloud for production offered a desirable combination of affordability and provided services, including confidence in terms of infrastructure reliability and the high availability assurance.
  2. Developer experience
    Throughout the entire internal proof-of-concept (PoC) process, the developer experience was a key aspect for evaluation. Meilisearch proved to be advantageous for Qogita as it provided a convenient Python library which simplified the migration process. Setting up containers on Meilisearch Cloud was also a straightforward task. Additionally, Meilisearch's vibrant and engaged open source community served as a significant advantage, establishing trust within Qogita's team early on.
  3. Product cadence and roadmap
    Qogita’s team was impressed by the speed with which Meilisearch was able to achieve feature parity with the alternatives, despite being one of the youngest search solutions on the market. Additionally, Meilisearch presented a solid roadmap that included several features aligned with the value envisioned by Qogita's team for its search initiatives in the near future.

Implementation and moving to Meilisearch Cloud

Qogita initially self-hosted to evaluate if Meilisearch fulfilled its requirements in terms of development experience. Following the evaluation, production was migrated to Meilisearch Cloud, providing Qogita's team with peace of mind regarding infrastructure outsourcing. The transition from Algolia and the rollout of Meilisearch production went seamlessly, maintaining a high level of internal developer satisfaction.

Results and Vision

Qogita highlighted higher developer satisfaction as one of the main benefits of choosing Meilisearch Cloud as their search provider, with ease of integration and out-of-the-box relevancy being key contributing factors.

The engineering department's goal was to ensure accurate data and product delivery, as well as providing the best user experience in connecting buyers and sellers through the platform. Meilisearch empowered Qogita team to deliver lightning-fast and highly relevant search results, tailored to meet the specific needs of their customers.

In terms of their vision for search efforts, Qogita expressed that the upcoming facet value search feature (coming to Meilisearch in v1.3) would enhance the user search experience even further. Facets allow customers to refine search results by multiple categories simultaneously. For a company like Qogita, which carries tens of thousands of brands in its catalog, facet search will enable the display and exposure of a greater number of brands to users, with further improved relevancy.

Globally, AI innovation is gaining prominence, and Qogita's team envisions a future that involves contextual search, meaningful search suggestions, and personalization. Meilisearch's upcoming vector search release marks an exciting venture into the AI space, aiming to fulfill these requirements and provide fast and relevant search for AI-powered applications.