Pricing

Clean your AMQP data streams automatically, thanks to your AI agents

Swiftask connects natively to your AMQP queues. Your AI agents intercept, clean, and normalize incoming messages in real time.

Result:

Eliminate corrupted data and ensure optimal quality for your downstream systems.

Raw AMQP data is often unusable

Messages flowing through your AMQP buses come from heterogeneous sources. They often contain format errors, missing values, or non-normalized structures. Manual cleaning or complex scripts are slow, expensive, and difficult to maintain.

Main negative impacts:

Degraded data quality: Dirty data injected into your databases or analytics tools skews results and decisions.
Maintenance complexity: Custom cleaning scripts quickly become obsolete as message formats evolve.
Processing latency: Heavy cleaning processes slow down message distribution, impacting your system's overall reactivity.

Swiftask deploys intelligent AI agents that filter, clean, and structure AMQP messages on the fly, before they reach your storage or analytics systems.

BEFORE / AFTER

What changes with Swiftask

Without Swiftask

A message arrives on the AMQP queue with an incorrect format. It is ingested as is, causing errors in the receiving application. A technical team must intervene, correct the message, and restart the process manually.

With Swiftask + AMQP

The message is captured by the Swiftask agent. The AI identifies anomalies, corrects errors, normalizes the format, and forwards the cleaned message to the destination queue. All this happens in milliseconds.

How to automate AMQP cleaning in 4 steps

STEP 1 : Create your cleaning agent

Define cleaning and normalization rules in Swiftask. Configure what constitutes valid or invalid data.

STEP 2 : Connect your AMQP broker

Configure secure access to your AMQP queues (RabbitMQ, Qpid, etc.) directly in Swiftask.

STEP 3 : Configure the processing pipeline

Define the input queue to monitor and the output queue for cleaned messages.

STEP 4 : Activate and monitor

The agent processes messages continuously. Track success rates and detected anomalies via the dashboard.

AI cleaning capabilities

The AI analyzes message schema, detects type anomalies, outliers, and structural inconsistencies.

Target connector: The agent performs the right actions in amqp based on event context.
Automated actions: Format normalization (JSON, XML, CSV). Duplicate removal. Missing data enrichment. Schema transformation. Conditional routing based on quality.
Native governance: Every operation is logged to ensure full traceability of changes made to the data.

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

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

1. Guaranteed data quality

Only compliant data reaches your critical systems.

2. Real-time performance

Ultra-fast processing with no bottlenecks.

3. Reduced costs

Fewer manual interventions and corrective maintenance tasks.

4. AI adaptability

The AI adapts to format changes without recoding.

5. Governance and audit

Full history of every data transformation.

Data security

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

Secure connection: Full TLS support for your AMQP connections.
Data isolation: Data is processed in a secure environment.
Traceability: Full audit logs for compliance.

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

RESULTS

Impact on your data flows

Metric	Before	After
Data error rate	High (recurring errors)	Close to 0% (automated)
Processing time	Manual / Batch scripts	Real-time (milliseconds)
Maintenance	Intensive development	No-code configuration

Take action with amqp

Eliminate corrupted data and ensure optimal quality for your downstream systems.