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Boost search relevance with Deep Tagger and Swiftask

Swiftask integrates Deep Tagger to turn raw documents into structured assets. Find exactly what you need, instantly.

Result:

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.

Main negative impacts:

  • Unsuccessful searches: Employees spend hours looking for documents that already exist, due to poor indexing.
  • Information silos: Data is scattered and uncorrelated, preventing a comprehensive view of company knowledge.
  • Productivity loss: Time spent searching is time stolen from value creation and strategic analysis.

The Swiftask + Deep Tagger integration automates semantic tagging of your documents. Every file is analyzed, classified, and enriched, making your knowledge base finally actionable.

BEFORE / AFTER

What changes with 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

STEP 1 : Connect your sources to Deep Tagger

Centralize your documents (PDF, Docx, Emails) in your Swiftask space connected to Deep Tagger.

STEP 2 : Define your tag schemas

Configure the business categories and entities that Deep Tagger should automatically extract from your content.

STEP 3 : Intelligent background indexing

Deep Tagger analyzes, tags, and structures every new incoming document without human intervention.

STEP 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).

  • Target connector: The agent performs the right actions in deep tagger based on event context.
  • Automated actions: Automatic metadata extraction. Hierarchical document classification. Contextual search based on NLP understanding. Automatic mapping of relationships between documents.
  • Native governance: All these operations are invisible to the end-user who simply benefits from high-performance search.

Each action is contextualized and executed automatically at the right time.

Each Swiftask agent uses a dedicated identity (e.g. agent-deep-tagger@swiftask.ai ). You keep full visibility on every action and every sent message.

Key takeaway: The agent automates repetitive decisions and leaves high-value actions to your teams.

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 applies enterprise-grade security standards for your deep tagger automations.

  • Localized processing: Your documents are processed in compliance with your company's security policies.
  • Access management: Indexing respects the original access permissions of each document.
  • Data integrity: Deep Tagger adds metadata without altering the original content of your files.
  • Auditability: Every tag added by the AI is traceable to ensure process transparency.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Impact on your document efficiency

MetricBeforeAfter
Search timeSeveral minutesA few seconds
Relevance rateLow (high noise)Very high (targeted)
Tag updatesManual (rare)Automatic (real-time)
Structured data volumePartial100% of the base

Take action with deep tagger

Eliminate data silos and reduce document retrieval time by 80%.

Ensure data compliance with Deep Tagger and AI

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