Smart keyword extraction with Dandelion and Swiftask
Turn raw text into structured data. Connect your AI agents to Dandelion to automatically extract entities and relevant keywords.
Result:
Save hours of manual analysis and improve the accuracy of your content indexing.
AI Agents
dandelion
Connector dandelion · Secure OAuth 2.0
Manual keyword extraction stalls your productivity
Manually analyzing thousands of documents to extract primary topics is tedious, error-prone, and impossible to scale for a modern enterprise.
Main negative impacts:
Tag inconsistency
Without automation, every team member uses different criteria, making your document databases unusable.
High operational costs
The time teams spend manually tagging articles or reports represents a disproportionate human investment.
Unstructured data
A lack of relevant keywords prevents effective search and limits the discoverability of your strategic content.
Through the Dandelion connector, Swiftask automates complex keyword extraction. Your AI agent processes documents in real-time, ensuring consistent and intelligent classification.
BEFORE / AFTER
What changes with Swiftask
Traditional management
An analyst reads each document, identifies key terms, then manually enters them into your CMS or CRM. Typing errors are frequent and the volume processed is limited by human reading speed.
Automation with Swiftask
As soon as a document is uploaded, the Swiftask AI agent queries Dandelion. Keywords are extracted, normalized, and injected directly into your business tools without any human intervention.
Deploy your extraction pipeline in 4 steps
1
STEP 1 : Initialize your AI agent
Set up an agent in Swiftask dedicated to text analysis and categorization.
2
STEP 2 : Integrate the Dandelion API
Connect Dandelion to your agent to leverage its advanced NLP and keyword extraction capabilities.
3
STEP 3 : Define processing rules
Configure the relevance threshold and the desired output format for your keywords.
4
STEP 4 : Automate your workflows
Link the data output to your target applications (database, CRM, SEO tools).
Advanced semantic analysis features
The agent evaluates the frequency, contextual relevance, and semantic reach of each term extracted by Dandelion.
- Target connector: The agent performs the right actions in dandelion based on event context.
- Automated actions: Named entity extraction, key concept identification, relevance score by word, tag normalization, multilingual support.
- Native governance: All analyses are logged in Swiftask to allow performance audits on the quality of your indexing.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-dandelion@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.
Major operational benefits
Increased semantic precision
Benefit from Dandelion's NLP power for extraction far more accurate than simple frequency algorithms.
Massive time savings
Free your teams from repetitive indexing tasks to focus on strategic analysis.
Unlimited scalability
Process thousands of documents per hour without increasing your headcount.
Data standardization
Ensure consistent taxonomy across your entire information assets.
Seamless integration
Easily connect the extraction process to your existing software ecosystem via Swiftask.
Compliance and data security
Swiftask applies enterprise-grade security standards for your dandelion automations.
- Secure processing: Exchanges between Swiftask and Dandelion are encrypted and compliant with B2B security standards.
- Access governance: Precisely control who can configure extraction agents and access the results.
- GDPR compliance: Swiftask ensures that text processing adheres to your company's privacy policies.
- Robust architecture: An infrastructure designed for high availability and protection of your sensitive data.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your key performance indicators
| Metric | Before | After |
|---|---|---|
| Processing time per doc | 5-10 minutes | Under 2 seconds |
| Indexing error rate | High (human) | Negligible (AI) |
| Doc volume processed | Limited by staff | Unlimited |
| Cost per extraction | High | Reduced by 90% |
Take action with dandelion
Save hours of manual analysis and improve the accuracy of your content indexing.