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Automate your content tagging with the power of AI

Swiftask integrates with Deep Tagger to classify, index, and organize your documents automatically, freeing your teams from manual data entry.

Resultat:

Boost productivity and optimize data accessibility through intelligent, consistent classification.

Document chaos is slowing down your growth

Manual tagging is a source of errors and inconsistencies. Without an automated system, documents pile up without actionable metadata, making information retrieval tedious.

Les principaux impacts négatifs :

  • Inefficient information retrieval: Poorly tagged documents are invisible documents. Your teams waste valuable time searching for files lost in disorganized folders.
  • Data inconsistency: Every user has their own tagging logic. The result: a fragmented knowledge base that is impossible to leverage for analysis.
  • Hidden operational costs: The time spent manually classifying files represents a significant cost that hinders your organization's innovation and agility.

Thanks to the Swiftask and Deep Tagger integration, your documents are analyzed and tagged automatically upon creation or receipt. The AI applies a consistent taxonomy, instantly.

AVANT / APRÈS

Ce qui change avec Swiftask

Manual tagging management

A team member receives a report. They must read the document, choose tags from a list that is sometimes outdated, then apply them. If they forget or make a mistake, the document becomes unfindable.

Automation with Swiftask + Deep Tagger

The document is uploaded. The Swiftask agent sends it to Deep Tagger, which extracts key entities and applies relevant tags. The document is immediately indexed and ready for retrieval.

Enable your tagging automation in 4 steps

ÉTAPE 1 : Configure your agent in Swiftask

Create an agent dedicated to document management. Define the document types to monitor and classification goals.

ÉTAPE 2 : Integrate Deep Tagger

Connect Deep Tagger to your Swiftask workflow. Configure the taxonomy or let the AI learn your classification standards.

ÉTAPE 3 : Define the trigger

Choose the trigger: new file in a cloud, email reception, or form submission. The agent detects new content.

ÉTAPE 4 : Deployment and monitoring

Activate the flow. Track tagging performance from the Swiftask dashboard and adjust precision if necessary.

Advanced capabilities of your tagging agent

The agent analyzes semantic content, document structure, and existing metadata to ensure multidimensional classification.

  • Connecteur cible : L'agent exécute les bonnes actions dans deep tagger selon le contexte de l'événement.
  • Actions automatisées : Automatic entity extraction (names, dates, amounts). Application of hierarchical tags. Metadata normalization. Automatic routing of documents to the correct folders.
  • Gouvernance native : The agent learns continuously from your validations to improve its classification accuracy over time.

Chaque action est contextualisée et exécutée automatiquement au bon moment.

Chaque agent Swiftask utilise une identité dédiée (ex. agent-deep-tagger@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.

Operational benefits of automated tagging

1. Instant search

Find any document in seconds thanks to rigorous, automated indexing.

2. Data homogeneity

Apply a uniform taxonomy across your entire organization, without the risk of human error.

3. Supercharged productivity

Eliminate repetitive entry and classification tasks so your teams focus on high-value analysis.

4. Improved governance

Stay in control of your data with complete traceability of every tagging action performed by the agent.

5. Effortless scalability

Manage thousands of documents a day without adding human resources: the AI scales with your needs.

Data security and compliance

Swiftask applique des standards de sécurité enterprise pour vos automatisations deep tagger.

  • Secure processing: Your documents are processed via encrypted connections. Swiftask guarantees the integrity of your files.
  • Access control: Define granular access rights for your agents and workspace users.
  • Full audit trail: Every tag applied is logged to ensure total traceability compliant with audit requirements.
  • Guaranteed privacy: Your data is not used to train third-party models without your explicit consent.

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

RÉSULTATS

Impact on your document performance

MétriqueAvantAprès
Classification timeSeveral minutes per documentUnder 5 seconds
Tagging precisionVariable (human error)Consistent (standardized)
Search timeHigh (manual search)Minimal (search by tag)
Management costHigh labor costOptimized and predictable

Passez à l'action avec deep tagger

Boost productivity and optimize data accessibility through intelligent, consistent classification.

Structurez vos données automatiquement avec Deep Tagger

Cas d'usage suivant.