Analyze and optimize your AI agent performance with ncScale
Swiftask partners with ncScale to provide full visibility into your models. Measure, analyze, and improve your agents' precision and speed.
Result:
Boost operational efficiency by identifying model bottlenecks in real-time.
AI Agents
ncscale
Connector ncscale · Secure OAuth 2.0
The lack of visibility into AI performance
Without precise data, it is impossible to know why an AI agent fails or slows down. Most companies deploy models without proper monitoring in place.
Main negative impacts:
Unpredictable latency
Variable response times that hinder user experience and team productivity.
Hidden operational costs
Poorly optimized models consume more resources than necessary, impacting your overall ROI.
Degradation of precision
A drop in response quality without early warning, leading to costly errors.
The Swiftask + ncScale integration allows you to monitor your agents, analyze performance metrics, and adjust your models based on hard data.
BEFORE / AFTER
What changes with Swiftask
Without performance analysis
You deploy an agent without monitoring tools. If performance drops, you only find out through user complaints. Diagnosis takes days.
With Swiftask + ncScale
You benefit from a centralized dashboard. Anomalies are detected instantly and latency metrics are analyzed in real-time.
Optimize your models in 4 simple steps
1
STEP 1 : Connect ncScale to Swiftask
Enable the ncScale connector in your Swiftask space with a few clicks to start data collection.
2
STEP 2 : Define your key metrics
Choose the metrics to monitor: latency, error rate, token consumption, or response accuracy.
3
STEP 3 : Analyze data flows
Use the ncScale dashboard to visualize agent behavior and identify bottlenecks.
4
STEP 4 : Adjust and iterate
Optimize prompts or model configuration in Swiftask based on the insights gathered.
Advanced analysis tools from ncScale
A 360° view of your AI interactions: response time per request, success rates, and granular error analysis.
- Target connector: The agent performs the right actions in ncscale based on event context.
- Automated actions: Real-time performance tracking. Automatic alerting for degradation. Comparative analysis of model versions. Full history for audit.
- Native governance: All data is centralized, allowing you to correlate performance with your deployments.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-ncscale@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 duo for your AI?
Data-driven decisions
Stop guessing, start measuring. Optimize your models with tangible proof.
Reduced latency
Identify the slowest requests and optimize your architecture for maximum speed.
Better ROI
Reduce resource waste by optimizing your AI model usage.
Increased reliability
Anticipate problems before they impact your end users.
Continuous improvement
Create a constant feedback loop to evolve your agents toward excellence.
Security and privacy
Swiftask applies enterprise-grade security standards for your ncscale automations.
- Encrypted data: Your performance data travels through secure channels.
- Compliance: Adherence to the strictest B2B data protection standards.
- Controlled access: Manage who accesses performance reports within your organization.
- Integrity: No changes to your models without your explicit validation.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your operations
| Metric | Before | After |
|---|---|---|
| Anomaly detection | Reactive (complaints) | Proactive (alerts) |
| Diagnostic time | Several hours | A few minutes |
| Cost optimization | Manual management | Data-driven |
| Model stability | Variable | Optimized and consistent |
Take action with ncscale
Boost operational efficiency by identifying model bottlenecks in real-time.