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%.
AI Agents
deep tagger
Connector deep tagger · Secure OAuth 2.0
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
1
STEP 1 : Connect your sources to Deep Tagger
Centralize your documents (PDF, Docx, Emails) in your Swiftask space connected to Deep Tagger.
2
STEP 2 : Define your tag schemas
Configure the business categories and entities that Deep Tagger should automatically extract from your content.
3
STEP 3 : Intelligent background indexing
Deep Tagger analyzes, tags, and structures every new incoming document without human intervention.
4
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
Increased search precision
Don't just find keywords; find documents that match your business need.
Operational time savings
Drastically reduce time spent navigating through file trees.
Knowledge capitalization
Transform your dormant archives into a living, structured knowledge base.
Automated scalability
The system handles data enrichment regardless of incoming document volume.
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
| Metric | Before | After |
|---|---|---|
| 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 |
Take action with deep tagger
Eliminate data silos and reduce document retrieval time by 80%.