Clean your Peliqan data automatically with AI agents
Swiftask integrates with Peliqan to automate the cleaning, normalization, and validation of your datasets in real time.
Result:
Save hours on data preparation and ensure flawless quality for all your analyses.
AI Agents
peliqan
Connector peliqan · Secure OAuth 2.0
Manual Peliqan data cleaning slows down your projects
Data preparation in Peliqan is often a major bottleneck. Between removing duplicates, fixing formats, and handling missing values, your team spends more time fixing data than using it.
Main negative impacts:
Recurring human errors
Manual handling introduces biases and errors that skew your analysis and decision-making reports.
Operational time loss
Repetitive cleaning consumes valuable resources that could be allocated to high-value tasks.
Loss of trust
If data is unclean, your team loses confidence in the insights generated by your tools.
Swiftask turns Peliqan into a source of clean data. Our AI agents apply intelligent cleaning rules upon ingestion, ensuring constant integrity.
BEFORE / AFTER
What changes with Swiftask
Without Swiftask
A data analyst manually exports data from Peliqan, uses Python scripts or Excel to clean columns, then re-imports the file. The process is slow, error-prone, and hard to maintain.
With Swiftask + Peliqan
Swiftask monitors your Peliqan tables. As soon as new data is added, the AI agent automatically applies the defined cleaning rules. Your data is ready to use instantly.
Set up your cleaning workflow in 4 steps
1
STEP 1 : Connect Peliqan to Swiftask
Link your Peliqan instance to Swiftask via our secure connector to access your tables and datasets.
2
STEP 2 : Define your cleaning rules
Configure instructions for your AI agent: date formatting, duplicate removal, text normalization, and value validation.
3
STEP 3 : Automate execution
Enable the trigger: cleaning runs automatically upon every update or according to a scheduled frequency.
4
STEP 4 : Monitor quality
Track cleaning reports in Swiftask. Receive alerts if anomalies are detected in your data.
Advanced features for your data
The AI agent analyzes the semantics and structure of the data to apply intelligent corrections, going beyond simple filters.
- Target connector: The agent performs the right actions in peliqan based on event context.
- Automated actions: Intelligent deduplication based on similarity. Automatic formatting normalization (phone, email, dates). Intelligent imputation of missing values. Cross-column consistency validation.
- Native governance: All transformations are documented in Swiftask for full traceability (audit trail).
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-peliqan@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 Swiftask for Peliqan?
Increased reliability
Drastically reduce error rates in your critical datasets.
No-code scalability
Handle growing data volumes without adding technical burden to your IT team.
Productivity gains
Automate 100% of repetitive and tedious cleaning tasks.
Full control
Define your own business rules and adjust them in just a few clicks.
Enhanced compliance
Ensure your data is clean to meet regulatory and governance requirements.
Data security and governance
Swiftask applies enterprise-grade security standards for your peliqan automations.
- End-to-end encryption: Data moving between Peliqan and Swiftask is protected by banking-grade security standards.
- Access control: Precisely control which agents have access to sensitive Peliqan tables.
- Action logs: Every cleaning operation is logged for complete and transparent auditing.
- GDPR compliance: Swiftask adheres to data protection standards, ensuring the security of your personal information.
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 | Hours per dataset | Seconds |
| Input error rate | High (manual) | Near zero (AI) |
| Data freshness | Delayed | Real-time |
| Human intervention | Daily | Supervision only |
Take action with peliqan
Save hours on data preparation and ensure flawless quality for all your analyses.