ConfigCat Data Integration — Feature Flag Insights
Connect ConfigCat and let AI agents query feature flag usage, evaluation metrics, and rollout data alongside product analytics from 1,000+ sources.
Key Takeaways Connect ConfigCat integration seamlessly
Improvado connects to ConfigCat's Management API to extract feature flag usage, evaluation metrics, user targeting data, and configuration changes. The platform automatically syncs data on your preferred schedule—hourly, daily, or custom intervals. No manual data exports or API development required. Your ConfigCat feature flag analytics flow directly into your data warehouse or BI tool.
Unified feature flag data across environments
Improvado's Marketing Common Data Model (MCDM) standardizes ConfigCat metrics alongside data from application monitoring, analytics platforms, and development tools. Feature flag evaluations, user segments, and rollout performance align with consistent naming conventions across all your data sources. This normalization enables comprehensive product analysis and feature adoption tracking in unified dashboards.
Data objects and fields Improvado extracts from ConfigCat
| Object | Fields |
|---|---|
| Feature Flag | key name hint setting_type value enabled |
| Environment | environment_id name color description |
| Product | product_id name description order |
| Setting | setting_id key name hint setting_type order |
From connection to autonomous action in three steps
Connect
Connect ConfigCat using your API key from the dashboard. The agent accesses feature flags, targeting rules, and rollout percentages across all environments in read-write mode.
Ask
Ask questions like 'Which flags are currently in gradual rollout?' or 'What's the user distribution for payment feature flags in production?' The agent queries flag states, environment configs, and user segment targeting.
Act
The agent adjusts rollout percentages, enables or disables flags across environments, updates targeting rules, creates flag variations, and triggers rollbacks when performance thresholds are breached.
What teams ask their AI agent about ConfigCat
Real prompts from enterprise marketing teams. The agent reads your data, answers in seconds, and takes action when you ask.
Track feature adoption rates across user segments to optimize product rollout strategies
Your AI agent analyzes ConfigCat data and delivers actionable insights — automatically, in seconds.
Analyze feature flag performance impact on conversion rates and user engagement metrics
Your AI agent analyzes ConfigCat data and delivers actionable insights — automatically, in seconds.
Generate product reports combining feature usage with business KPIs and user behavior
Your AI agent analyzes ConfigCat data and delivers actionable insights — automatically, in seconds.
Your agent doesn't just read ConfigCat — it measures feature impact on KPIs.
Read
The agent reads feature flag states, rollout percentages, targeting rules, environment configurations, user segment distributions, flag evaluation counts, and historical flag changes across all connected projects.
Write
The agent modifies rollout percentages, enables or disables feature flags, updates targeting rules and conditions, creates new flag variations, schedules gradual rollouts, and executes emergency rollbacks across specified environments.
Monitor
The agent monitors flag evaluation volumes, rollout progression against performance thresholds, user segment behavior under flag variations, environment-specific flag states, and conversion or error rate changes tied to flag deployments.
AI agents query feature flag evaluations, targeting rules, and configuration changes from ConfigCat. They can analyze feature adoption by user segment, correlate flag rollouts with conversion rate changes, and answer "Did enabling the new checkout feature increase revenue for premium users?" by connecting flags with business metrics.
| Flag Name | Rollout % | Impact |
|---|---|---|
| express_checkout_v2 | 100% | +4.2% CVR |
| apple_pay_integration | 75% | +8.1% CVR |
| one_click_upsell | 50% | +2.7% AOV |
| guest_checkout_flow | 25% | +1.9% CVR |
| saved_payment_methods | 10% | +3.4% CVR |
Send ConfigCat data anywhere
Load normalized data to your preferred warehouse, BI tool, or cloud storage. Click any destination to see its integration guide.
They extract data. Improvado deploys an agent.
Traditional tools move data from A to B. Improvado gives you an AI agent that reads, acts, and monitors — with ConfigCat as one of 1,000+ integrated sources.
| Feature | Improvado | Supermetrics | Funnel.io | Fivetran |
|---|---|---|---|---|
| Data fields extracted | 200+ | ~90 | ~120 | ~80 |
| Total integrations | 1,000+ | ~150 | ~500 | ~300 |
| Cross-channel normalization (CDM) | ✓ Built-in | ✗ Manual | ● Basic mapping | ✗ Raw only |
| AI Agent access (MCP) | ✓ Read, Write, Monitor | ✗ | ✗ | ✗ |
| Data warehouse destinations | ✓ 16+ warehouses & BI tools | Sheets, Looker, BigQuery | BigQuery, Snowflake, Redshift | ✓ Broad warehouse support |
| Refresh frequency | Every 15 min | Scheduled triggers | Daily / 6hr | Every 15 min (premium) |
| SOC 2 Type II & HIPAA | ✓ | ✗ SOC 2 only | ✓ SOC 2 | ✓ |
| Best for | Teams that want an AI agent, not a pipeline | Small teams, spreadsheets | Mid-market, data teams | Engineering-led ELT pipelines |
Comparison based on publicly available documentation as of April 2026. Feature availability may vary by plan tier.
Frequently asked questions
What ConfigCat data can Improvado extract?
How often does Improvado sync ConfigCat data?
Can I combine ConfigCat data with application analytics?
Does Improvado handle ConfigCat API authentication?
What destinations work with ConfigCat data integration?
How does Improvado transform ConfigCat evaluation data?
"Improvado saves about 90 hours per week and allows us to focus on data analysis."
"Improvado's reporting tool effortlessly integrates all our marketing data so we can easily track users across their entire digital journey. This saves me and my team countless hours."
Put an AI agent on your ConfigCat today
Connect in under 5 minutes. Your agent starts reading, acting, and monitoring immediately.