Swiftask integrates Deep Tagger to turn raw documents into structured assets. Find exactly what you need, instantly.
Resultat:
Eliminate data silos and reduce document retrieval time by 80%.
The challenge of finding information in a data deluge
The volume of internal documents is exploding, but the ability to find them is lagging. Misnamed files, missing metadata, and siloed systems turn every search into a frustrating waste of time for your teams.
Les principaux impacts négatifs :
The Swiftask + Deep Tagger integration automates semantic tagging of your documents. Every file is analyzed, classified, and enriched, making your knowledge base finally actionable.
AVANT / APRÈS
Ce qui change avec Swiftask
Classic search: the chaos
You type a keyword into your search tool. You get 500 irrelevant results because documents aren't tagged correctly. You have to open each file to check if it's the right one.
Swiftask + Deep Tagger search: the precision
Deep Tagger has automatically identified the context, entities, and value of each document. Your Swiftask search understands your intent and only offers truly relevant documents.
4 steps to transform your internal search
ÉTAPE 1 : Connect your sources to Deep Tagger
Centralize your documents (PDF, Docx, Emails) in your Swiftask space connected to Deep Tagger.
ÉTAPE 2 : Define your tag schemas
Configure the business categories and entities that Deep Tagger should automatically extract from your content.
ÉTAPE 3 : Intelligent background indexing
Deep Tagger analyzes, tags, and structures every new incoming document without human intervention.
ÉTAPE 4 : Semantic search enabled
Use the Swiftask search engine to query your enriched knowledge base with unprecedented precision.
Advanced optimization capabilities
Deep Tagger analyzes textual content, but also semantic context, tone, and named entities (clients, projects, dates, amounts).
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.
Strategic benefits for the enterprise
1. Increased search precision
Don't just find keywords; find documents that match your business need.
2. Operational time savings
Drastically reduce time spent navigating through file trees.
3. Knowledge capitalization
Transform your dormant archives into a living, structured knowledge base.
4. Automated scalability
The system handles data enrichment regardless of incoming document volume.
5. Compliance and governance
Better tagging allows for tighter control of access to sensitive documents based on their metadata.
Data security and integrity
Swiftask applique des standards de sécurité enterprise pour vos automatisations deep tagger.
Pour aller plus loin sur la conformité, consultez la page gouvernance Swiftask et ses détails d'architecture de sécurité.
RÉSULTATS
Impact on your document efficiency
| Métrique | Avant | Après |
|---|---|---|
| Search time | Several minutes | A few seconds |
| Relevance rate | Low (high noise) | Very high (targeted) |
| Tag updates | Manual (rare) | Automatic (real-time) |
| Structured data volume | Partial | 100% of the base |
Passez à l'action avec deep tagger
Eliminate data silos and reduce document retrieval time by 80%.