Extract key entities automatically with Lettria and your AI agents
Swiftask integrates with Lettria to turn your raw text into structured data. Automatically identify entities, locations, organizations, and concepts in your data flows.
Result:
Save hours of manual analysis and structure your data for rapid decision-making.
AI Agents
lettria
Connector lettria · Secure OAuth 2.0
Manual text data management hinders your productivity
Your teams receive thousands of documents, emails, and feedback entries daily. Manually extracting key information (names, amounts, dates, products) is a monotonous task that creates errors and unacceptable delays.
Main negative impacts:
Cognitive overload and errors
Repetitive manual extraction inevitably leads to data entry errors and operational fatigue.
Unusable data silos
Valuable information remains trapped in unstructured files, preventing trend analysis or effective reporting.
Limited customer responsiveness
Time spent processing information delays responses to customer requests and critical issue resolution.
With the Swiftask and Lettria integration, you automate entity extraction. Your AI agents scan, identify, and categorize information instantly, with no code required.
BEFORE / AFTER
What changes with Swiftask
The traditional process
A team member receives an email or report. They must read it, manually identify relevant entities, and copy them into an Excel file or CRM. This process is slow, error-prone, and not scalable.
The Swiftask + Lettria automation
As soon as text arrives, your Swiftask agent sends it to Lettria. Entities are extracted in milliseconds and automatically injected into your business tools. Your data is ready for analysis.
Set up your extraction pipeline in 4 steps
1
STEP 1 : Define your agent in Swiftask
Create a dedicated extraction agent. Configure it to monitor your incoming data sources (emails, APIs, forms).
2
STEP 2 : Configure the Lettria connector
Enable the Lettria module in Swiftask to leverage cutting-edge Natural Language Processing (NLP) capabilities.
3
STEP 3 : Set parameters for extraction
Select the types of entities to capture (e.g., company names, dates, products) to customize analysis for your business needs.
4
STEP 4 : Automate the output flow
Define where extracted data should be sent: CRM, database, or Slack for immediate notification.
Advanced analysis capabilities for your data
Lettria provides deep semantic understanding, going beyond simple keyword searching to identify the real context of every entity.
- Target connector: The agent performs the right actions in lettria based on event context.
- Automated actions: Multi-language extraction, custom Named Entity Recognition (NER), associated sentiment analysis, data normalization, and seamless integration with your storage tools.
- Native governance: All extraction steps are monitored within Swiftask, ensuring total transparency regarding the quality of processed data.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-lettria@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 advantages of automated extraction
Increased precision
AI eliminates human errors related to manual text data entry.
Unlimited scalability
Process massive text volumes without increasing headcount or operational costs.
Data monetization
Transform raw text into structured assets for your decision-making dashboards.
Operational agility
Drastically reduce processing time, allowing for faster response to opportunities or incidents.
Frictionless integration
No-code allows business teams to configure their own extraction workflows without IT intervention.
Data security and privacy
Swiftask applies enterprise-grade security standards for your lettria automations.
- End-to-end encryption: Your text data is protected during transfer between Swiftask and Lettria.
- GDPR compliance: The architecture is designed to meet European standards for data protection.
- Access control: Manage fine-grained access permissions for extraction pipelines within your organization.
- Audit and traceability: Every extraction is logged to ensure full visibility into your information processing.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Measurable impact on efficiency
| Metric | Before | After |
|---|---|---|
| Processing time per document | 5 to 10 minutes | Under 2 seconds |
| Error rate | 5-10% (human) | Under 0.1% (AI) |
| Volume of processed data | Limited by human capacity | Unlimited, 24/7 |
| Operational ROI | High management costs | Significant cost reduction |
Take action with lettria
Save hours of manual analysis and structure your data for rapid decision-making.