Tarification

Index your databases for high-performance AI

Swiftask's EmbedAPI transforms your structured and unstructured data into semantic vectors. Give your AI deep knowledge of your business.

Resultat:

Accelerate response times and dramatically improve the relevance of your AI agents.

The limits of traditional text search

Traditional keyword search often fails to understand the real intent behind a query. Without semantic indexing, your AI ignores business context, document relationships, and language nuances.

Les principaux impacts négatifs :

Irrelevant results: AI provides superficial answers because it doesn't grasp the underlying meaning of your business data.
Information silos: Your data is scattered and inaccessible to your AI agents, slowing down automation.
Processing bottlenecks: Scanning massive databases without vector indexing is costly and inefficient.

Swiftask's EmbedAPI automates the vectorization and indexing of your databases. Your documents become vectors ready for instant semantic search.

AVANT / APRÈS

Ce qui change avec Swiftask

Without vector indexing

Your AI performs rigid text search. It misses synonyms, related concepts, and complex contexts, generating mediocre results.

With EmbedAPI + Swiftask

Each piece of data is indexed in a vector space. The AI understands meaning, semantic proximity, and delivers precise answers based on your documents.

Deploy your AI indexing in 4 steps

ÉTAPE 1 : Connect your data sources

Link your databases (SQL, NoSQL, files) to Swiftask's EmbedAPI.

ÉTAPE 2 : Automated vectorization

The API transforms your data into high-performance embeddings in real-time.

ÉTAPE 3 : Semantic indexing

Vectors are stored in your vector database optimized for search.

ÉTAPE 4 : Intelligent querying

Your AI agents now query the index for instant, contextual answers.

EmbedAPI technical power

Intelligent chunking management, native multi-language support, and precise semantic alignment.

Connecteur cible : L'agent exécute les bonnes actions dans embedapi selon le contexte de l'événement.
Actions automatisées : On-the-fly vectorization, incremental index updates, support for hybrid search (keyword + vector).
Gouvernance native : Optimized for minimal latency and maximum precision.

Chaque action est contextualisée et exécutée automatiquement au bon moment.

Chaque agent Swiftask utilise une identité dédiée (ex. agent-embedapi@swiftask.ai ). Vous gardez une visibilité complète sur chaque action et chaque message envoyé.

À retenir : L'agent automatise les décisions répétitives et laisse à vos équipes les actions à forte valeur.

Strategic benefits for your business

1. Increased precision

Perfect contextual understanding of your internal data.

2. Unlimited scalability

Index millions of documents without performance degradation.

3. Seamless integration

RESTful API designed to fit into your current technical stack.

Security and data sovereignty

Swiftask applique des standards de sécurité enterprise pour vos automatisations embedapi.

Full encryption: Data secured at rest and in transit.
Access control: Granular management of index access permissions.

Pour aller plus loin sur la conformité, consultez la page gouvernance Swiftask et ses détails d'architecture de sécurité.

RÉSULTATS

Measurable performance

Métrique	Avant	Après
Search precision	50-60%	95%+
Response time	Seconds	Milliseconds

Passez à l'action avec embedapi

Accelerate response times and dramatically improve the relevance of your AI agents.

Analysez vos logs système instantanément avec la puissance de l'IA

Cas d'usage suivant.