Tarification

Extract essential keywords from your text with Datumbox

Swiftask automates document analysis via Datumbox. Instantly identify key concepts to better classify and leverage your data.

Resultat:

Save valuable time on document classification and improve the relevance of your internal searches.

Manual content indexing is inefficient

With the accumulation of reports, emails, and articles, manually extracting keywords is an impossible task. Manual processing is slow, prone to human error, and prevents consistent indexing of your knowledge base.

Les principaux impacts négatifs :

Loss of critical data: Without systematic extraction, important information remains buried in non-indexed documents, becoming invisible to your team.
Expensive indexing processes: Mobilizing human resources to manually tag every document represents a high operational cost that doesn't scale.
Inconsistent metadata: Each collaborator uses their own terms, making global search inefficient and chaotic within the organization.

Swiftask integrates Datumbox's analysis power to automate keyword extraction. Your texts are analyzed continuously, with consistent precision and a uniform structure.

AVANT / APRÈS

Ce qui change avec Swiftask

The manual approach

An analyst receives a report. They read it, mentally select the important terms, and manually enter them into a management system. It's a repetitive, slow task that depends entirely on human availability.

Swiftask + Datumbox automation

As soon as a new document is uploaded, Swiftask sends it to Datumbox. The AI instantly extracts relevant keywords and saves them directly to your database or CRM. Zero intervention, 100% precision.

Deploy your extraction pipeline in 4 steps

ÉTAPE 1 : Workflow initialization

Define the source of your documents in Swiftask: emails, cloud folders, or web forms.

ÉTAPE 2 : Datumbox connection

Integrate your Datumbox API key into Swiftask to access advanced text analysis capabilities.

ÉTAPE 3 : Rule configuration

Configure the relevance threshold for desired keywords and the output format for your data.

ÉTAPE 4 : Active automation

The system processes every new document in real-time. Your keywords are ready to be used for search.

Advanced analysis features

The Datumbox engine analyzes syntactic structure and semantic frequency to isolate the entities and concepts most representative of the document.

Connecteur cible : L'agent exécute les bonnes actions dans datumbox selon le contexte de l'événement.
Actions automatisées : Extraction of unique keywords, relevance weighting, identification of named entities, and direct integration of tags into your business tools (Notion, SQL databases, Airtable).
Gouvernance native : The solution ensures total uniformity of your metadata, facilitating cross-analysis across your entire document collection.

Chaque action est contextualisée et exécutée automatiquement au bon moment.

Chaque agent Swiftask utilise une identité dédiée (ex. agent-datumbox@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 advantages for your business

1. Real-time indexing

Your documents are immediately actionable upon receipt thanks to automated indexing.

2. Reduced operational costs

Eliminate manual entry and dedicate your resources to higher value-added tasks.

3. Improved internal search

Thanks to standardized keywords, the quality of your internal searches becomes instantly superior.

4. Scalability without limits

Whether you process ten or ten thousand documents, Swiftask automation maintains the same performance.

5. Seamless integration

Connect extraction results to any tool in your existing technology stack.

Data security and privacy

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

Secure processing: Your data is processed via encrypted connections between Swiftask and Datumbox.
Strict compliance: We adhere to data protection standards, ensuring the confidentiality of your content.
Total control: You maintain control over the documents sent and the data extracted.
Robust architecture: Infrastructure designed for high availability and the protection of your information flows.

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

RÉSULTATS

Measurable impact of automation

Métrique	Avant	Après
Processing time per document	5 to 10 minutes	Less than 2 seconds
Indexing precision	Variable (human)	Standardized (AI)
Documents processed per hour	Limited by entry	Unlimited
Cost per document	High (man-time)	Near zero

Passez à l'action avec datumbox

Save valuable time on document classification and improve the relevance of your internal searches.

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