Generate your V7 Go performance reports automatically
Swiftask connects your AI agents to V7 Go. Consolidate your annotation metrics and produce detailed reports without any manual effort.
Result:
Save hours every week. Get a clear view of your project velocity and data quality.
AI Agents
v7 go
Connector v7 go · Secure OAuth 2.0
Manual V7 Go performance tracking is a time sink
Managing large-scale annotation projects requires perfect visibility. Yet, extracting data from V7 Go, cleaning it, and formatting it into a report remains a repetitive, time-consuming task for project managers.
Main negative impacts:
Operational time loss
Teams spend hours exporting CSVs and creating charts instead of optimizing annotation workflows.
Outdated reporting
Data is often processed with delays, preventing agile decision-making regarding label quality.
Lack of granularity
It is difficult to quickly correlate annotator velocity with dataset complexity without automated tools.
Swiftask automates the extraction and analysis of your V7 Go metrics. Your AI agents generate structured performance reports, delivered directly to your decision-making teams.
BEFORE / AFTER
What changes with Swiftask
Without Swiftask
The project manager logs into V7 Go every Monday morning. They download exports, import them into a spreadsheet, apply complex formulas to calculate velocity per annotator, and then write a summary email.
With Swiftask + V7 Go
The Swiftask AI agent triggers automatically on a schedule. It pulls data via API, analyzes performance trends, generates a summary report, and shares it immediately on your communication channels.
4 steps to automate your V7 Go reports
1
STEP 1 : Configure your analysis agent
Create a dedicated reporting agent in Swiftask. Define the key performance indicators (KPIs) to track.
2
STEP 2 : Connect your V7 Go instance
Integrate Swiftask with V7 Go securely. The agent accesses your project data in read-only mode.
3
STEP 3 : Define generation frequency
Schedule your reports (daily, weekly) or trigger them based on a specific event in V7 Go.
4
STEP 4 : Share your insights
Choose the format and delivery channel: email, Slack, Teams, or internal dashboard.
Capabilities of your Swiftask AI agents
The agent processes raw V7 Go data to identify patterns: average time per image, error rates, progress per dataset, and workload per annotator.
- Target connector: The agent performs the right actions in v7 go based on event context.
- Automated actions: Automatic velocity calculation. Anomaly detection in annotations. Executive summary generation. Cross-project performance comparison.
- Native governance: All analyses are based on real data extracted from your V7 Go instance.
Each action is contextualized and executed automatically at the right time.
Each Swiftask agent uses a dedicated identity (e.g. agent-v7-go@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.
Strategic advantages of automated reporting
Fast decision-making
Access fresh data to adjust your annotation strategies in real time.
Increased productivity
Free your team from manual report preparation to focus on improving data quality.
Data governance
Ensure constant traceability of your AI project performances.
Standardization
All your projects use the same report templates, making comparison easier.
Scalability
Manage an increasing number of projects without increasing administrative burden.
Data security and compliance
Swiftask applies enterprise-grade security standards for your v7 go automations.
- Secure API connection: Swiftask uses restricted API tokens to interact with V7 Go.
- Environment isolation: Your annotation data remains siloed within your Swiftask workspace.
- Compliance: The system adheres to B2B security standards for handling sensitive data.
To learn more about compliance, visit the Swiftask governance page for detailed security architecture information.
RESULTS
Impact on your operational efficiency
| Metric | Before | After |
|---|---|---|
| Report preparation time | 4-8 hours/week | Automated (minutes) |
| Reporting frequency | Weekly (limited) | On-demand or real-time |
| Data accuracy | Human error risk | 100% reliability (machine processing) |
Take action with v7 go
Save hours every week. Get a clear view of your project velocity and data quality.