Pricing

Automated data cleaning with Swiftask and Ikigai

Swiftask orchestrates your data flows to Ikigai for intelligent cleaning. Transform raw data into reliable assets, instantly.

Result:

Save hours of manual preparation and eliminate human errors in your analytical processes.

Manual data preparation slows down your decisions

Data cleaning is a repetitive and time-consuming task. Between inconsistent formats, duplicates, and missing values, your teams spend more time fixing files than analyzing them.

Main negative impacts:

Critical inconsistencies: Poorly cleaned data leads to erroneous reports and strategic decisions based on flawed foundations.
Productivity loss: Data analysts and engineers spend 80% of their time on manual prep instead of high-value analysis.
Compliance risks: Manual handling increases the risk of input errors and non-compliance with data quality standards.

The Swiftask + Ikigai integration automates your cleaning pipelines. Define your rules once, and let AI agents process your data flows continuously.

BEFORE / AFTER

What changes with Swiftask

The manual workflow

Retrieving CSV files, manual correction on Excel, checking for duplicates, re-importing. This cycle repeats with every new dataset, creating a constant bottleneck.

The Swiftask + Ikigai workflow

As soon as data arrives, Swiftask sends it to Ikigai. Cleaning is applied automatically according to your business rules. Clean data is ready for your BI tools.

Four steps to automate your cleaning

STEP 1 : Define the flow

Configure the entry point for your raw data in Swiftask.

STEP 2 : Connect Ikigai

Associate your Ikigai instance as your data processing engine.

STEP 3 : Configure rules

Establish cleaning criteria: filtering, deduplication, normalization.

STEP 4 : Continuous deployment

Activate automation. Swiftask monitors and processes your data 24/7.

Intelligent processing capabilities

The agent analyzes the dataset structure to apply the right transformations.

Target connector: The agent performs the right actions in ikigai based on event context.
Automated actions: Intelligent deduplication, format normalization (dates, currencies), outlier correction, automatic enrichment via API.
Native governance: Every step of the process is tracked for total transparency on data quality.

Each action is contextualized and executed automatically at the right time.

Each Swiftask agent uses a dedicated identity (e.g. agent-ikigai@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.

Operational benefits

1. Increased reliability

Drastic reduction in human-related errors.

2. Scalability

Process thousands of rows without extra effort.

3. Time saving

Free your teams for strategic analysis missions.

4. Standardization

Unify your data across all departments.

5. Agility

Adjust cleaning rules in a few clicks without code.

Data governance

Swiftask applies enterprise-grade security standards for your ikigai automations.

End-to-end encryption: Your data is protected throughout the transfer.
Full traceability: Detailed audit logs for every cleaning operation.
Access management: Granular control over who can modify cleaning rules.
GDPR compliance: Architecture designed to meet data protection standards.

To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.

RESULTS

Impact on your performance

Metric	Before	After
Preparation time	Hours per project	Minutes (real-time)
Error rate	High	Near zero
Data volume	Human-limited	Unlimited
Operational cost	Human hourly cost	Reduced by 70%

Take action with ikigai

Save hours of manual preparation and eliminate human errors in your analytical processes.

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