Clean and structure your text data with Lettria and Swiftask
Swiftask orchestrates your data flows to Lettria, transforming raw text into actionable insights without manual effort.
Result:
Improve your AI model quality and accelerate analysis by automating your corpus cleaning.
AI Agents
lettria
Connector lettria · Secure OAuth 2.0
The complexity of cleaning unstructured data
Processing large volumes of text (customer reviews, support tickets, legal docs) is hindered by noisy, unformatted, or inconsistent data. Manual cleaning is impossible at scale, and custom scripts quickly become unmanageable.
Main negative impacts:
Unusable data
Noise in your datasets drastically reduces the accuracy of your machine learning models and semantic analyses.
High operational costs
Using engineers to manually clean data or maintain fragile pipelines is a waste of valuable resources.
Slow time to market
Data preparation is often the bottleneck that delays the deployment of your AI projects.
Swiftask connects your data sources to the Lettria platform. Cleaning, normalization, and enrichment processes are automated in a fluid and scalable pipeline.
BEFORE / AFTER
What changes with Swiftask
Without automation
You manually extract data from various sources, export to CSV, and attempt to clean it using scattered Python scripts. The lack of standardization makes every new dataset complex to process, lengthening preparation cycles.
With Swiftask + Lettria
As soon as new data is collected, Swiftask automatically triggers a workflow to Lettria. Text is cleaned, normalized, and structured instantly. Your data is ready to use, without any additional technical intervention.
Automate your data pipelines in 4 steps
1
STEP 1 : Connect your sources to Swiftask
Configure your connectors (email, CRM, API) in Swiftask to centralize your text data streams.
2
STEP 2 : Integrate Lettria as your processing engine
Use the native Lettria integration to define cleaning, lemmatization, and entity extraction rules.
3
STEP 3 : Define the transformation workflow
Set up the flow: data reception, processing by Lettria, and routing to your database or analytics tool.
4
STEP 4 : Monitor quality in real time
Track the volume of processed data and cleaning accuracy directly from your Swiftask dashboard.
Advanced capabilities for your datasets
The workflow analyzes syntax, context, and semantic relevance for every entry to ensure a clean and rich final dataset.
- Target connector: The agent performs the right actions in lettria based on event context.
- Automated actions: Automatic text noise removal, data format normalization, named entity recognition (NER), automatic classification, and semantic enrichment.
- Native governance: All transformations are auditable. You maintain full traceability from source data to cleaned output.
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.
Why choose this duo for your data
Increased accuracy
Lettria ensures high-quality cleaning, boosting the reliability of all downstream analyses.
Full scalability
Process thousands of documents per hour without changing your infrastructure.
Massive time savings
Your data scientists focus on analysis and modeling rather than tedious manual cleaning.
Standardization
Your data is uniform, facilitating integration across your various business tools.
Business agility
Adapt your cleaning rules in a few clicks via Swiftask's no-code interface.
Data security and compliance
Swiftask applies enterprise-grade security standards for your lettria automations.
- Encrypted flows: All data moving between Swiftask and Lettria is encrypted in transit and at rest.
- GDPR friendly: Cleaning processes can include automatic anonymization of personal data.
- Granular control: You choose exactly which data is sent for processing.
- Robust infrastructure: Architecture designed for high availability and enterprise data security.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your data operations
| Metric | Before | After |
|---|---|---|
| Preparation time | Several days | A few minutes |
| Data quality | Variable and noisy | Standardized and structured |
| Throughput | Manual / Limited | Automated / Unlimited |
| Maintenance cost | High (manual scripts) | Low (no-code pipeline) |
Take action with lettria
Improve your AI model quality and accelerate analysis by automating your corpus cleaning.