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Clean and normalize your RelationCity data automatically with AI

Swiftask integrates with RelationCity to identify, correct, and harmonize your data in real time. Maintain a reliable database without manual intervention.

Result:

Eliminate duplicates, fix entry errors, and ensure the integrity of your critical data continuously.

Degraded RelationCity data is expensive

An unmaintained RelationCity database degrades quickly: duplicates, inconsistent formats, outdated information. This clutter prevents your teams from making informed decisions and reduces campaign effectiveness.

Main negative impacts:

  • Reduced sales efficiency: Erroneous data leads to targeting mistakes, useless follow-ups, and a damaged brand image with prospects.
  • High maintenance costs: Manual cleansing is slow, repetitive, and prone to human error, consuming resources on low-value tasks.
  • Decisions based on false data: Without a clean foundation, your analytics and reporting lose all relevance, compromising your growth strategy.

Swiftask automates the cleansing of your RelationCity data. Your AI agents detect anomalies, normalize formats, and merge duplicates according to your business rules, ensuring a single source of truth.

BEFORE / AFTER

What changes with Swiftask

Without Swiftask

Your teams spend hours every week manually checking RelationCity records, correcting typos, and deleting duplicates. Despite these efforts, errors persist and the database remains fragmented.

With Swiftask + RelationCity

Your AI agent continuously monitors entries in RelationCity. As soon as data fails to meet your standards, it is automatically corrected or flagged for validation. Your database stays healthy, effortlessly.

4 steps to automate your cleansing

STEP 1 : Define your quality rules

Configure your data standards in Swiftask: address format, name normalization, deduplication rules.

STEP 2 : Connect your RelationCity instance

Activate the secure connector between Swiftask and RelationCity. Swiftask accesses necessary data to perform audits.

STEP 3 : Configure the cleaning agent

The agent scans your database, identifies anomalies in real time, and applies defined corrections or alerts you in case of conflict.

STEP 4 : Monitor data health

Check the Swiftask dashboard to track the volume of data processed and corrections made daily.

Intelligent cleaning capabilities

The agent analyzes each entry to detect inconsistencies, potential duplicates, and formatting errors based on your business rules.

  • Target connector: The agent performs the right actions in relationcity based on event context.
  • Automated actions: Automatic duplicate merging, format normalization (phones, emails, addresses), spell checking, missing data enrichment, audit reports.
  • Native governance: All cleaning actions are logged for full transparency and rollback capabilities if needed.

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

Each Swiftask agent uses a dedicated identity (e.g. agent-relationcity@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 automate with Swiftask

1. Increased reliability

Your teams work with data that is always up-to-date, accurate, and ready to use.

2. Massive time savings

Automate data entry and cleaning tasks to free your staff for strategic missions.

3. Guaranteed compliance

Ensure data consistency to meet data protection standards and internal processes.

4. Scalability

The system processes thousands of entries instantly without slowing down your daily operations.

5. Unified governance

Control cleaning rules from a single interface and adapt them as your business needs evolve.

Security and integrity

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

  • Secure API connection: The integration respects RelationCity's security standards to ensure your information is protected.
  • Validation rules: You retain final control: approve automatic corrections or set the agent to autonomous mode.
  • Modification traceability: Every correction is recorded with a complete history, facilitating data auditing.
  • Data isolation: Swiftask processes your data in a secure, siloed environment, ensuring confidentiality.

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

RESULTS

Impact on your efficiency

MetricBeforeAfter
Time spent cleaningSeveral days/monthsMinutes (supervision)
Input error rateHigh (manual)Near zero (automated)
Database qualityUnstableCertified and consistent
Team productivityLow (repetitive tasks)Maximal (value-driven)

Take action with relationcity

Eliminate duplicates, fix entry errors, and ensure the integrity of your critical data continuously.

Anticipate customer needs in RelationCity with AI

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