Smart data filtering for Keboola using AI
Swiftask integrates with Keboola to automatically filter and qualify your data streams. Get clean, relevant datasets for your business decisions.
Result:
Remove noise from your data and accelerate your analysis with automated semantic filtering.
AI Agents
keboola
Connector keboola · Secure OAuth 2.0
Manual management of massive Keboola datasets
Data pipelines often generate excessive volumes of useless or poorly structured information. Manual filtering via complex scripts is slow, expensive, and error-prone, slowing down your decision-making.
Main negative impacts:
Information overload
Your analysis tools are cluttered with raw data that hides the weak signals essential to your strategy.
Complex transformation scripts
Constant maintenance of SQL or Python filtering scripts increases the workload for Data Engineering teams.
Gap between data and business needs
Lack of contextual filtering makes reports difficult for non-technical decision-makers to interpret.
Swiftask acts as an intelligence layer over your Keboola flows. Our AI agents filter, classify, and clean data at the source based on your business rules, before it even reaches your warehouse.
BEFORE / AFTER
What changes with Swiftask
Traditional Keboola management
You extract all raw data. A technical team must then write and maintain complex transformations to isolate relevant information, creating bottlenecks.
Augmented management with Swiftask
The AI agent analyzes the Keboola stream in real time. It applies smart filters based on business context, keeping only high-value data for your analysis.
Deploy AI filtering in 4 steps
1
STEP 1 : Initialize your agent in Swiftask
Define the business filtering criteria and data quality goals for your AI agent.
2
STEP 2 : Connect your Keboola buckets
Establish a secure gateway between your Keboola instance and Swiftask to access data streams.
3
STEP 3 : Set transformation rules
Configure the filtering thresholds and cleaning logic that the AI must systematically apply.
4
STEP 4 : Automate the output flow
Re-inject filtered data into Keboola or send it directly to your destination applications.
Semantic analysis capabilities
The AI evaluates the relevance of each data row, identifies anomalies, and normalizes formats dynamically.
- Target connector: The agent performs the right actions in keboola based on event context.
- Automated actions: Keyword or entity filtering, smart deduplication, data enrichment, automatic classification, real-time anomaly detection.
- Native governance: Each filtering operation is logged in Swiftask to ensure total transparency on data transformation.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-keboola@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.
Competitive advantages of AI filtering
Increased data quality
Drastically reduce errors and inconsistencies in your datasets.
Data Engineering agility
Free your engineers from repetitive cleaning script maintenance tasks.
Reduced storage costs
Process and store only the data useful for your business.
Rapid decision-making
Access clean, ready-to-use insights in record time.
No-code scalability
Instantly adapt your filtering rules as your business needs evolve.
Security and data governance
Swiftask applies enterprise-grade security standards for your keboola automations.
- End-to-end encryption: All data transiting between Keboola and Swiftask is encrypted according to industry standards.
- Strict compliance: Filtering respects your privacy policies and GDPR regulations.
- Full traceability: A complete audit history allows you to track every applied filtering rule.
- Isolated architecture: Swiftask operates in a secure environment ensuring the integrity of your datasets.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your data operations
| Metric | Before | After |
|---|---|---|
| Processing time | Several hours (scripts) | Real time (AI) |
| Useless data volume | 30-50% of total | Less than 5% |
| Technical maintenance | Weekly | Zero (no-code) |
| Insight reliability | Variable | Optimized (99%+) |
Take action with keboola
Remove noise from your data and accelerate your analysis with automated semantic filtering.