Master your structured data with AI and Swiftask
Swiftask integrates with Inferable to transform your raw, complex data into actionable structures. Automate your data pipelines without a single line of code.
Result:
Increase reliability, reduce human error, and accelerate data-driven decision-making.
AI Agents
inferable
Connector inferable · Secure OAuth 2.0
Data complexity is slowing you down
Many companies waste valuable time manually cleaning, formatting, and structuring data from disparate sources. This manual process is not only slow, but also prone to errors, impacting the quality of your insights and business decisions.
Main negative impacts:
Errors in data entry and formatting
Manual manipulation introduces inconsistencies that skew your reporting and business tools.
Costly and slow processes
Time spent by your teams restructuring data is time lost for higher-value tasks.
Data not usable in real-time
Manual processing delays prevent immediate use of information, slowing down your business agility.
With the Swiftask and Inferable integration, you automate data structuring. Your AI agents process, clean, and organize your information continuously, ensuring reliable data is instantly available.
BEFORE / AFTER
What changes with Swiftask
Before automation
Your teams receive raw data via email or APIs. They must manually clean it, transform it into the required format, and import it into your systems, creating bottlenecks.
With Swiftask + Inferable
Upon receipt, data is automatically processed by your AI agents. It is structured, validated, and injected directly into your business tools. The process is seamless, immediate, and error-free.
How to structure your data in 4 steps
1
STEP 1 : Define your schema in Swiftask
Configure the desired output structure for your data. The AI agent will learn to transform raw inputs according to this model.
2
STEP 2 : Connect Inferable
Enable the Inferable connector in Swiftask to allow your agents to interact with your complex data streams.
3
STEP 3 : Automate the pipeline
Configure triggers so the agent processes new data as soon as it arrives, with zero manual intervention.
4
STEP 4 : Monitor and validate
Track data processing via the Swiftask dashboard. Maintain full control over the quality of the information produced.
Key data management features
The AI analyzes content, detects anomalies, and applies complex transformation rules to standardize your streams.
- Target connector: The agent performs the right actions in inferable based on event context.
- Automated actions: Data extraction from various formats. Automatic normalization. Validation based on business rules. Direct injection into your databases or CRM.
- Native governance: Every operation is tracked and logged, ensuring total compliance and visibility into the transformation history.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-inferable@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.
Benefits for your business
Increased precision
Eliminate human error with automation based on strict business rules.
Operational time savings
Free your teams from repetitive data entry and cleaning tasks.
Continuously actionable data
Instantly transform raw streams into data assets ready for analysis.
No-code scalability
Adapt your data pipelines to company growth without needing complex development.
Enhanced governance
Centralize and audit all your data streams within a single interface.
Security and compliance
Swiftask applies enterprise-grade security standards for your inferable automations.
- Data encryption: All processed data is encrypted, ensuring total confidentiality of your critical information.
- Strict access control: Fine-tune permissions for access to data pipelines via Swiftask.
- Full traceability: Access a detailed history of every transformation for internal audits.
- Compliance: Meet data protection standards with a secure and isolated architecture.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Measurable impact of automation
| Metric | Before | After |
|---|---|---|
| Data processing time | Several hours per day | A few seconds |
| Error rate | Variable and significant | Near zero |
| Data availability | Delayed (D+1) | Real-time |
| Human effort | Manual and intensive | Supervision only |
Take action with inferable
Increase reliability, reduce human error, and accelerate data-driven decision-making.