VP Engineering data analysis without SQL complexity
AI workspace that turns questions into dashboards, reports, and actionable engineering insights
Backed by the best
Engineering data bottlenecks slow decisions
Your engineering metrics live in GitHub, BigQuery, and monitoring tools, but getting answers requires SQL queries, dashboard building, or waiting for analysts. Sprint velocity analysis takes hours of manual work. Performance metrics require custom scripts. Infrastructure cost breakdowns need complex joins across multiple data sources. Simple questions like 'which teams ship fastest?' become multi-day projects.
- Sprint velocity analysis requires manual GitHub API calls and spreadsheet work
- Performance metrics need custom scripts to correlate deployment and monitoring data
- Infrastructure cost breakdowns require complex BigQuery joins across billing tables
- Team productivity comparisons take days of manual data collection and analysis
Turn engineering questions into instant insights and automated reports
- Ask 'show sprint velocity by team' and get automated dashboards with GitHub integration
- Get performance analysis that correlates deployment data with monitoring metrics automatically
- Generate infrastructure cost reports with team attribution and trend analysis
- Create recurring engineering KPI reports that update automatically every sprint
- Build custom tools for engineering analysis that your team can reuse
How it works
- 01
Connect data sources
Authenticate GitHub, BigQuery, monitoring tools through guided setup conversations
- 02
Ask engineering questions
Request analysis in natural language, AI builds queries and reports automatically
- 03
Get automated insights
Receive dashboards, scheduled reports, and reusable analysis tools for your team
What Brainvolt brings to your workflow
Contextual Engineering Intelligence
AI draws from GitHub commits, BigQuery metrics, and monitoring data in one analysis. Correlates deployment frequency with performance metrics while citing all data sources.
Code Execution And Automation
Builds Python scripts for custom analysis, creates SQL queries for complex reports, and automates recurring engineering metrics collection without manual coding.
Engineering Tool Integrations
Pre-built connections to GitHub, BigQuery, Google Analytics, and monitoring platforms. Creates new integrations on-demand for internal tools and custom APIs.
Compounding Engineering Knowledge
Remembers analysis patterns, builds reusable tools from solved problems, and accumulates engineering metrics knowledge across your organization over time.
Frequently asked questions
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Get things done.
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