Perform A/B testing on your AI models with Swiftask and Orq.ai
Stop guessing which model performs best. Compare your prompts and models in real-world conditions to ensure the best user experience.
Result:
Improve your AI agent accuracy and cut operational costs through data-driven evaluation.
AI Agents
orq.ai
Connector orq.ai · Secure OAuth 2.0
The uncertainty of choosing the right AI model
Selecting the best model for a specific task is often an empirical process. Without a robust comparison method, you risk deploying underperforming or expensive agents without knowing how to optimize them.
Main negative impacts:
Unpredictable performance
Without A/B testing, it is impossible to objectively quantify the accuracy gains between two prompt versions or different models.
Uncontrolled costs
Using the most powerful model by default is inefficient. You end up paying for intelligence you don't always need.
Slow iteration cycles
The lack of a dedicated testing platform hinders innovation and delays the rollout of AI-powered features.
The Swiftask + Orq.ai integration automates your A/B tests. Route your requests to different models simultaneously and analyze results in a unified interface.
BEFORE / AFTER
What changes with Swiftask
Traditional approach
You test a prompt change manually in a chat interface. You record results in an Excel sheet without rigorous variable control, leading to biased conclusions.
Swiftask + Orq.ai approach
Your agents dynamically switch between two models or prompt versions. Performance metrics (latency, accuracy, cost) are collected automatically for reliable statistical analysis.
4 steps to orchestrate your A/B tests
1
STEP 1 : Define variants
Set up your model or prompt variants in Orq.ai. Swiftask sends the requests to the corresponding endpoints.
2
STEP 2 : Traffic distribution
Use routing tools to distribute user requests between your different versions.
3
STEP 3 : Metrics collection
Swiftask and Orq.ai capture key metrics: response time, token usage, and user relevance scores.
4
STEP 4 : Analyze and decide
Visualize results in your dashboards. Identify the winning variant and deploy to production with one click.
Advanced testing capabilities
Comparative evaluation based on latency, token consumption, and response success rates.
- Target connector: The agent performs the right actions in orq.ai based on event context.
- Automated actions: Intelligent request routing, side-by-side output comparison, prompt version management, and real-time monitoring.
- Native governance: The integration ensures perfect synchronization between Swiftask workflows and Orq.ai observability features.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-orq.ai@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 choose this approach?
Evidence-based decisions
Make decisions based on actual statistics rather than gut feelings.
Cost optimization
Identify the lightest model capable of meeting your quality requirements.
Continuous improvement
Refine your prompts continuously to improve end-user satisfaction.
Safe deployment
Test new versions on a fraction of traffic before a full rollout.
Full observability
Keep track of every test, every variant, and its impact on performance.
Testing security and governance
Swiftask applies enterprise-grade security standards for your orq.ai automations.
- Data isolation: Your tests are isolated and do not compromise live production systems.
- Compliance: Strict access control to test data via Swiftask roles.
- Audit trail: Full history of model changes and test results.
- Stability: Resilient architecture ensuring your tests do not impact service availability.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Success indicators
| Metric | Before | After |
|---|---|---|
| Average latency | Variable and unmeasured | Optimized and stable |
| Response accuracy | Subjective | Measurable (0-100 score) |
| Cost per request | Fixed (often too high) | Reduced by using optimal model |
| Iteration time | Days | Hours |
Take action with orq.ai
Improve your AI agent accuracy and cut operational costs through data-driven evaluation.