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Meilisearch

  • What it is:Meilisearch is an open-source search engine written in Rust featuring a blazing fast RESTful API, typo tolerance, and AI-powered hybrid search.
  • Best for:Developer teams building search features, Startups and MVPs, Cost-conscious mid-size apps
  • Pricing:Free tier available, paid plans from $30/month
  • Rating:82/100Very Good
  • Expert's conclusion:Meilisearch is best suited for developers and forward-thinking companies creating modern applications that require both high performance search and semantic intelligence and want the ability to deploy and customize easily.
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Reviewed byMaxim Manylov·Web3 Engineer & Serial Founder

What Is Meilisearch and What Does It Do?

Meilisearch is a Paris-based open-source search engine that was created by three experienced developers who were fed up with the complexity of existing search options. The team has created an ultra-fast and highly relevant search-as-a-service for web and mobile apps. The goal of the company is to provide all developers and businesses with access to a high quality search solution.

Active
📍Paris, France
📅Founded 2018
🏢Private
TARGET SEGMENTS
DevelopersStartupsEnterprisesE-commerce

What Are Meilisearch's Key Business Metrics?

📊
10M+
Downloads
📊
10,000+
Apps Relying on Meilisearch
📊
$22M
Total Funding
🏢
50 (target by 2023)
Employees

How Credible and Trustworthy Is Meilisearch?

82/100
Good

Strong developer adoption of the open-source platform along with venture capital funding, however very little publicly available information regarding revenue or user reviews.

BREAKDOWN
Product Maturity85/100
Company Stability80/100
Security & Compliance70/100
User Reviews75/100
Transparency90/100
Support Quality80/100
TRUST SIGNALS
10M+ downloads10,000+ apps in productionBacked by Felicis, CRV, SeedcampOpen source on GitHub

What is the history of Meilisearch and its key milestones?

2018

Company Founded

Meilisearch was founded by Quentin de Quelen, Clément Renault and Thomas Payet after they developed search capabilities at Veepee and Louis Vuitton.

2019

Beta Release

Meilisearch launched its beta as an open source search engine in Rust.

2020

Seed Funding

Meilisearch raised 1.5M € to develop the open source search functionality.

2022

Series A Funding

Meilisearch closed a $15M series A round led by Felicis to build out the Meilisearch Cloud and Enterprise versions.

2022

Meilisearch Cloud Launch

After closing the beta for its SaaS product Meilisearch released it to the public.

How Much Does Meilisearch Cost and What Plans Are Available?

Pricing information with service tiers, costs, and details
☐Service$CostℹDetails🔗Source
Build$30/month50,000 searches included, 100,000 documents included, overage $0.40/1K searches, $0.30/1K documents, community support, 7-day analyticsOfficial pricing page
Pro$300/month250,000 searches included, 1,000,000 documents included, overage $0.30/1K searches, $0.20/1K documents, priority chat/email support, 30-day analyticsOfficial pricing page
Custom EnterpriseCustom quoteSubscription-based or resource-based pricing, volume discounts, premier SLA support, SOC2 certified, tailored featuresOfficial pricing page
Free Trial14 daysFull access to paid features, no credit card required—
Self-Hosted Open Source$0Unlimited usage with your own infrastructure—
Build$30/month
50,000 searches included, 100,000 documents included, overage $0.40/1K searches, $0.30/1K documents, community support, 7-day analytics
Official pricing page
Pro$300/month
250,000 searches included, 1,000,000 documents included, overage $0.30/1K searches, $0.20/1K documents, priority chat/email support, 30-day analytics
Official pricing page
Custom EnterpriseCustom quote
Subscription-based or resource-based pricing, volume discounts, premier SLA support, SOC2 certified, tailored features
Official pricing page
Free Trial14 days
Full access to paid features, no credit card required
Self-Hosted Open Source$0
Unlimited usage with your own infrastructure

How Does Meilisearch Compare to Competitors?

FeatureMeilisearchElasticsearchAlgoliaTypesense
Core FunctionalityFast typo-tolerant searchDistributed search & analyticsAI search & recommendationsFast faceted search
Starting Price$30/moPay-as-you-go$0.50/1K searches~$7/mo
Free TierSelf-hosted OSSYes (basic)Pay-as-you-goSandbox
Enterprise FeaturesSOC2, Custom plansPremium securitySSO, Audit logsEnterprise plans
API AvailabilityYes (HTTP/REST)Yes (comprehensive)Yes (robust)Yes
Integration CountDeveloper SDKsEnterprise ecosystemExtensiveSDKs
Support OptionsPriority (paid)Enterprise SLAPremium supportEnterprise support
Security CertificationsSOC2Enterprise securitySOC2, GDPREnterprise security
Core Functionality
MeilisearchFast typo-tolerant search
ElasticsearchDistributed search & analytics
AlgoliaAI search & recommendations
TypesenseFast faceted search
Starting Price
Meilisearch$30/mo
ElasticsearchPay-as-you-go
Algolia$0.50/1K searches
Typesense~$7/mo
Free Tier
MeilisearchSelf-hosted OSS
ElasticsearchYes (basic)
AlgoliaPay-as-you-go
TypesenseSandbox
Enterprise Features
MeilisearchSOC2, Custom plans
ElasticsearchPremium security
AlgoliaSSO, Audit logs
TypesenseEnterprise plans
API Availability
MeilisearchYes (HTTP/REST)
ElasticsearchYes (comprehensive)
AlgoliaYes (robust)
TypesenseYes
Integration Count
MeilisearchDeveloper SDKs
ElasticsearchEnterprise ecosystem
AlgoliaExtensive
TypesenseSDKs
Support Options
MeilisearchPriority (paid)
ElasticsearchEnterprise SLA
AlgoliaPremium support
TypesenseEnterprise support
Security Certifications
MeilisearchSOC2
ElasticsearchEnterprise security
AlgoliaSOC2, GDPR
TypesenseEnterprise security

How Does Meilisearch Compare to Competitors?

vs Elasticsearch

Meilisearch serves developers that are looking for a simple search solution with predictable pricing. Elasticsearch, which is also used for search, is geared toward larger organizations that require complex analytics and distributed search capabilities. While Elasticsearch offers more analytics capability than Meilisearch, Meilisearch offers simpler pricing plans.

Meilisearch is designed for a developer-friendly search solution, while Elasticsearch is designed for enterprise-level analytics and scalability.

vs Algolia

Algolia offers AI powered recommendations and uses a pay-per-use pricing model. In contrast, Meilisearch offers a tiered pricing plan starting at $30 per month. Therefore, Meilisearch is generally less expensive for moderate use cases. However, Algolia's advanced personalization features are not available in Meilisearch.

Meilisearch is designed for cost-conscience teams, while Algolia is designed for organizations that require AI-powered recommendations.

vs Typesense

Direct competitors in the developer search space.

Meilisearch offers pricing flexibility, while Typesense is the least expensive option to enter the search space. Beginning of Text

What are the strengths and limitations of Meilisearch?

Pros

  • Pricing model — tiered pricing that has a fixed cost per month (starting at $30) with clear overage pricing.
  • Search performance — Meilisearch performs searches in less than 50 ms.
  • Developer-friendliness — Meilisearch uses an easy to use API and provides multiple SDK’s as well as great documentation.
  • Tolerance to typos — Meilisearch has auto-complete and auto-suggest functionality.
  • Enterprise pricing flexibility — you can choose either subscription based pricing or resource based pricing.
  • Self-hosting option — The core of Meilisearch is open source and therefore there are no licensing fees associated with using it.
  • Hosted cloud — You can have your search engine hosted by Meilisearch and get a 14 day free trial and instantly provision your search engine.

Cons

  • Overage pricing for usage — You will be charged extra for searching past the number of queries included in your pricing tier ($0.20-$0.40/1K).
  • Analytics limitations — While Meilisearch does provide some analytics data, this data is typically only available for a period of 7-30 days. This is compared to many other enterprise search solutions which retain their data for much longer periods.
  • Complex aggregations limited — Meilisearch focuses primarily on providing a search experience. If you need to perform complex aggregations, consider using a solution such as Elasticsearch.
  • Basic community support — If you want priority support, you must purchase the Pro plan for $300/month.
  • Limitations to search volume — The amount of queries you can perform within the included pricing tier may limit how large of a user base you can support with Meilisearch (included: 50K/250K).
  • Younger company — Meilisearch has fewer enterprise case studies to reference when compared to its older competitors.
  • Minimum resources required — Dedicated instances begin around $144/month.

Who Is Meilisearch Best For?

Best For

  • Developer teams building search features — Fast setup with SDKs and predictable pricing starting at $30/month
  • Startups and MVPs — 14 day free trial, self-hosting option, scalable with affordability.
  • Cost-conscious mid-size apps — More cost effective than Algolia’s pay-per-use pricing model due to its tiered pricing structure.
  • Teams avoiding infrastructure management — Instantly scale your search engine in the cloud with Meilisearch.
  • E-commerce sites needing typo-tolerant search — Great relevance rankings right out of the box.

Not Suitable For

  • High-volume enterprise analytics — Does not have all of the same aggregation capabilities as Elasticsearch. Use Elasticsearch or OpenSearch instead.
  • Ultra-low budget projects — Typesense is approximately $7/month cheaper than Meilisearch. Consider Typesense or self-hosting.
  • AI recommendation platforms — Less personalized than Algolia. Consider Algolia or Pinecone if you require more personalization in your search experience.
  • Teams needing complex business intelligence — Focuses on providing a search experience, not analytics. Use Elasticsearch.

Are There Usage Limits or Geographic Restrictions for Meilisearch?

Build Plan Searches
50,000/month included, $0.40 per 1,000 overage
Build Plan Documents
100,000 included, $0.30 per 1,000 overage
Pro Plan Searches
250,000/month included, $0.30 per 1,000 overage
Pro Plan Documents
1,000,000 included, $0.20 per 1,000 overage
Analytics Retention
7 days (Build), 30 days (Pro)
Support Level
Community Discord (Build), Priority chat/email (Pro)
Billing Granularity
Per project, not shared across account
Trial Period
14 days free, no credit card
Self-Hosting
No limits with own infrastructure
Compliance
SOC2 certified (Enterprise)

Is Meilisearch Secure and Compliant?

SOC 2 Type IIEnterprise plans include SOC2 certification for security, availability, and confidentiality
Data EncryptionTLS in transit, encryption at rest in managed cloud hosting
GDPR ComplianceEU data residency options available through cloud regions
Access ControlsAPI key authentication, project isolation in cloud plans
Cloud InfrastructureFully managed on secure cloud providers with automatic backups and redundancy
Audit Logging30-day monitoring metrics retention (Pro), search analytics available
Self-Hosted SecurityOpen source allows full control over security implementation and keys

What Customer Support Options Does Meilisearch Offer?

Channels
Comprehensive official documentation availableOpen-source repository with community support
Support Limitations
•Limited information available about dedicated support tiers and response times
•No evidence of 24/7 phone or live chat support

What APIs and Integrations Does Meilisearch Support?

API Type
RESTful API with comprehensive REST endpoints
SDKs
Official SDKs for JavaScript, Python, Go, PHP, Ruby, Rust, and other languages
Framework Integration
Tailored SDKs for React, Laravel, LangChain, and various frameworks
Authentication
API key-based authentication with fine-grained permissions
Security
Multi-tenancy support with security management and controlled user access
Documentation
Well-documented with interactive examples and tutorials
AI Integration
Works out-of-the-box with LangChain and Model Context Protocol
Use Cases
Full-text search, semantic search, hybrid search, vector embeddings, RAG applications, multi-modal search

What Are Common Questions About Meilisearch?

Meilisearch is an open-source search engine created using Rust that is designed to create fast, relevant search experiences. It returns search results in less than 50 ms and offers advanced search capabilities such as hybrid search, semantic search and typo tolerance.

Meilisearch delivers search results in under 50ms, i.e., much faster than the blink of an eye. The performance is consistent for both large scale/high volume searches and for complex queries.

Hybrid Search allows for Full-Text Keyword Searching combined with AI-based Semantic Searching, offering users the best of both worlds – relevant semantic matches, as well as results that include exact keyword matches will receive higher rankings and therefore help mitigate the potential for Vector-only searching to miss queries that depend on keyword(s).

Typo Tolerance is enabled by default in Meilisearch, providing users with results that are relevant even when queries include typos and/or misspellings. Typo Tolerance does not require configuration.

In addition to supporting extensive Multilingual Search, Meilisearch also includes optimized support for Chinese, Japanese, Hebrew, and all other languages utilizing the Latin Alphabet. Meilisearch can index/search data in virtually any language.

Meilisearch utilizes Artificial Intelligence-based searching through Vector Embeddings and NLP to determine context and intent behind the search query, and thus provide results based on what was searched for versus how it was phrased. Traditional Full-Text Search only returns documents that have been indexed specifically for the search terms queried, and may not include relevant search results for ambiguous/natural language queries.

Yes, Meilisearch offers very flexible Ranking Rule Customization and Faceting options. Users can sort their search results based on Price, Date, etc., and configure the Relevance Scoring to fit their specific application/requirement.

Yes, Meilisearch is very suitable for Ecommerce applications. Meilisearch’s features such as Faceted Search, Filtering by Multiple Attributes (Brand, Price, Specifications, etc.), Geosearch, and Fast Search-as-you-Type Functionality, all work together to enhance the user experience.

Meilisearch provides a Clean RESTful API, as well as SDK's for most major programming languages and Frameworks, to make integrating into an existing application, simple. Meilisearch can be up and running in minutes and can integrate with various frameworks including JavaScript, Python, Go, etc.

Meilisearch can be used for multi-modal search as well as text, allowing users to perform searches on different formats of content.

Is Meilisearch Worth It?

Meilisearch is a developer-friendly search engine that allows for fast, accurate search results with very little to no setup. It has hybrid search capabilities by utilizing a combination of keyword and semantic search along with smart default options such as typo-tolerant search and "search as you type", which makes it suitable for most modern application use cases. The open source nature of Meilisearch and its large suite of SDKs make it accessible to more users than other search engines.

Recommended For

  • E-commerce sites looking for quick product discovery with filtering options
  • SaaS sites requiring full-text and semantic search capabilities
  • Blogs, documentation, knowledge bases (content based sites)
  • Development teams wanting to add search functionality without needing to spend hours configuring it
  • Companies looking for modern search technology that will not bind them into a single vendor.
  • Sites requiring search of multiple languages and/or formats (images, video etc.)

!
Use With Caution

  • Enterprise level teams requiring custom support contracts and Service Level Agreements (SLA)
  • Companies that require their security to meet specific compliance standards — Verify security certifications
  • Sites requiring advanced user-based personalization that goes beyond what Meilisearch currently offers
  • Sites that do not have the internal IT staff to manage hosting and maintenance of the search infrastructure themselves.

Not Recommended For

  • Sites that require 24/7 phone support and a designated account manager
  • Sites that prioritize cost-effective search over feature rich search
  • Sites that don't need to utilize semantic search or AI features and can get away with just basic search functionality.
Expert's Conclusion

Meilisearch is best suited for developers and forward-thinking companies creating modern applications that require both high performance search and semantic intelligence and want the ability to deploy and customize easily.

Best For
E-commerce sites looking for quick product discovery with filtering optionsSaaS sites requiring full-text and semantic search capabilitiesBlogs, documentation, knowledge bases (content based sites)

What do expert reviews and research say about Meilisearch?

Key Findings

Meilisearch, a search engine built using Rust, has an open-source version that provides sub-50 ms response time to searches. Also, Meilisearch uses a combination of default settings such as "search as you type" (a search feature where results begin appearing before the user finishes typing) and "typo tolerance" (a setting that ignores minor spelling errors when conducting searches). A major advantage of Meilisearch is its hybrid search capability that combines both full-text and semantic search capabilities, with additional AI capabilities provided by companies such as OpenAI and Hugging Face. With Meilisearch, developers have the option to integrate their search into various development frameworks, including several popular ones, via a wide array of software developer kits (SDKs).

Data Quality

Excellent — comprehensive information from official website, documentation, GitHub repository, and multiple technical articles. Features and capabilities are well-documented with code examples and use cases.

Risk Factors

!
Limited information is available publicly regarding Meilisearch's support tiers and Service Level Agreements (SLA) for commercial use.
!
For users who do not purchase a paid subscription plan, they are responsible for self-hosting Meilisearch.
!
Meilisearch competes with other well-established search engines, such as Elasticsearch.
!
Meilisearch relies on third-party AI vendors to provide semantic search functionality.
Last updated: January 2026

What Additional Information Is Available for Meilisearch?

Open Source Community

Meilisearch is entirely open source, hosted on GitHub, and allows developers to make contributions, develop custom functionality, and host themselves.

AI-Ready Architecture

Because Meilisearch was designed around AI primitives, it can operate with LangChain and the Model Context Protocol without need for further configuration. In addition, Meilisearch supports vector embeddings and is positioned to support future hyper-personalization and advanced AI capabilities.

Geosearch Capabilities

Meilisearch supports geographically based filtering and sorting, which makes it a good fit for use within location aware applications, such as travel, real estate, and local service finder applications.

Default-On Performance

Unlike many of Meilisearch’s competitors that require extensive fine-tuning, Meilisearch comes with a variety of search features enabled by default, such as "typos tolerated", "prefix search", and "smart ranking", which greatly reduces the amount of work needed to create modern search experiences.

Easy Deployment

Developers can deploy Meilisearch in just a few minutes using the pre-configured “smart preset” to allow them to search data with no initial configuration, which is ideal for rapid prototyping or production use.

Use Case Versatility

Meilisearch is optimized for use in e-commerce, SaaS platform, and content driven applications, as well as for use in data-intensive dashboards. Meilisearch also includes facets, filters, synonyms, customizable sort options, and multiple tenancy for personalized search. Text is between the markers below BEGIN_TEXT

What Are the Best Alternatives to Meilisearch?

  • •
    Elasticsearch: A mature, standard industry search platform with a robust full-text search feature as well as advanced analytics options. The tool offers even more advanced search functions and a larger ecosystem, but has a much greater barrier to entry in terms of learning curve and resource consumption. Ideal for enterprise level deployments that have established search teams. (elastic.co)
  • •
    Algolia: Search hosted by the company providing fast, accurate results to developers. Provides proprietary SaaS solutions at a premium price point however does provide no need for self-hosting. Best for development teams requiring simple managed infrastructure rather than low-cost. (algolia.com)
  • •
    Typesense: An open source, typo tolerant search engine comparable to Meilisearch. Fast and developer friendly with instant search capabilities. Self-hosted or cloud based options are both available. Best suited for companies seeking an Algolia alternative where they can maintain some degree of control. (typesense.org)
  • •
    OpenSearch: A community driven open license fork of Elasticsearch. Similar to Elasticsearch however allows users to avoid being locked into a specific vendor. While more complex than Meilisearch it offers significantly more power for advanced uses cases. Ideal for organizations that require Elasticsearch functionality however want assurances from a third party vendor through open sourcing. (opensearch.org)
  • •
    Weaviate: A vector database specifically designed for the use cases associated with semantic search and artificial intelligence-based applications. Much stronger for machine learning applications and RAG applications however not nearly as strong as other tools for pure keyword searching. Ideal for companies who prioritize semantic searching and vector operations above traditional hybrid search. (weaviate.io)

What Are Meilisearch's Operational Performance Kpis?

<50ms ms
Query Latency (P99)
>1000 QPS
Throughput (Queries Per Second)
<100ms ms
Indexing Latency
<50ms ms
Embedding Generation Time
Scalable to millions of documents
Index Memory Footprint
>60% %
Cache Hit Rate
<0.1% %
Search Error Rate

What Core Search Capabilities Does Meilisearch Offer?

Hybrid Search (BM25 + Vector)

Supports semantic ratio which can be controlled using the semanticRatio parameter (0.0 - 1.0). This is a native integration with BM25 keyword search and vector semantic search.

Typo-Tolerant Search

Supports built in spell checking and fuzzy matching when returning hybrid results.

Semantic Similarity Matching

Uses vector embeddings with ANN for intent recognition and supports the user to create their own models such as Gemini.

Custom Ranking Rules

Allows the user to tune the system for their own business needs using the semanticRatio slider along with filters and rank controls.

Re-ranking with LLM Models

Can be achieved via a external pipeline after the Meilisearch retrieval process. It is not native.

Real-Time Index Updates

Supports instantaneous updating of documents without having to re-index the entire corpus.

Batch Indexing

Enables efficient bulk ingestions of data and provides 7 times faster performance compared to competing solutions when working with large volumes of data.

Multilingual Support (20+ languages)

Optimized tokenization for CJK, Hebrew, Latin languages in hybrid search

RAG Framework Integration

SDKs for LangChain, tailored integrations for vector retrieval in RAG

What Is Meilisearch's Technical Architecture Specs?

Vector Search Engine - Primary Algorithm
Approximate Nearest Neighbor (ANN)
Vector Search Engine - Supported Vector Dimensions
Custom dimensions via external embeddings
Vector Search Engine - Distance Metrics
Cosine similarity primary
Vector Search Engine - Maximum Vector Capacity
Scalable to millions via clustering
Keyword Search Technology - Ranking Algorithm
BM25
Keyword Search Technology - Tokenization
Language-aware for 20+ languages including CJK
Keyword Search Technology - Query Syntax
Full-text with filters, facets, typos
Embedding Model Support - Pre-trained Models
Gemini, OpenAI, Sentence-BERT via API integration
Embedding Model Support - Custom Model Support
Any model outputting vectors
Embedding Model Support - Model Inference
External service + Meilisearch storage/retrieval
Infrastructure Requirements - Deployment Options
Cloud SaaS, self-hosted Docker/Kubernetes
Infrastructure Requirements - Memory Per 1M Vectors
Efficient ANN storage, ~1-2GB base
Infrastructure Requirements - High Availability
Multi-region, clustering support
Infrastructure Requirements - GPU Support
External for embeddings; CPU-optimized core
Scalability Limits - Maximum Document Count
Billions via distributed deployment
Scalability Limits - Concurrent Queries
1000+ QPS per node, horizontally scalable
Scalability Limits - Index Update Frequency
Real-time per document

What Is Meilisearch's Compliance And Security Framework Status?

GDPR Compliance
CCPA Compliance
SOC 2 Type II
Encryption at Rest
Encryption in Transit
Role-Based Access Control (RBAC)
API Key Management
Comprehensive Audit Trails
Regional Data Isolation
Vulnerability Management

How Does Meilisearch's Use Case Suitability Matrix Compare?

Primary Use CaseKey RequirementsCritical MetricsRecommended Features
RAG (Retrieval-Augmented Generation)Fast vector retrieval, hybrid precision, LangChain SDK integrationLatency <50ms, Precision@5 >0.85, NDCGHybrid search, semanticRatio tuning, real-time updates
E-Commerce SearchTypo tolerance, conversion optimization, visual search potentialCTR >25%, conversion +43%, bounce <25%Hybrid BM25+vector, semanticRatio 0.3, multilingual
Customer Support & FAQ MatchingIntent understanding, search-as-you-type, low reformulationReformulation <15%, zero-results <3%High semanticRatio 0.9, typo tolerance
Content Discovery & RecommendationsSemantic matching beyond keywords, freshnessDwell time >30s, diversity ratio >70%Vector search, real-time indexing
Legal & Contract DiscoveryPrecise hybrid retrieval, self-hosting for sovereigntyPrecision@K >0.90, audit loggingCustom embeddings, RBAC
Healthcare Knowledge RetrievalFast accurate retrieval, regional deploymentOn-topic >0.90, latency <50msCustom domain models, multi-region
Academic Research & Literature SearchLarge-scale indexing, multilingual papersRecall@20, indexing speed 7x fasterBatch indexing, hybrid search
Internal Knowledge Base SearchEmployee-facing speed, typo toleranceCTR >30%, session <5minSearch-as-you-type, self-hosted

How Does Meilisearch's Embedding Model Selection Framework Compare?

Model CategoryExample ModelsVector DimensionsInference LatencyCost ProfileBest For
Open-Source (Local)Sentence-BERT, any HuggingFace384-102450-200ms CPUFree self-hostedMeilisearch self-hosted, cost control
API-Based (Commercial)Gemini, OpenAI text-embedding768-1536100-500ms API$0.02-$0.10/M tokensMeilisearch Cloud rapid deployment
Domain-Specific ModelsBioBERT, Legal-BERT768-1024100-300msFree/licensedVertical semantic search with Meilisearch
Large Language Models (LLM)Gemini embeddings integration1536+200-1000msAPI-based pricingHigh-accuracy Meilisearch hybrid setups
Hybrid/Cross-EncoderPost-retrieval re-rankers50ms per candidateLow volumePrecision boost after Meilisearch retrieval
Lightweight/DistilledMiniLM, DistilBERT38420-50msMinimalReal-time Meilisearch indexing

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