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AI-augmented offshore software-development firm offering agentic automation and Google Cloud, Chrome, and Zoom enterprise services.
Documentation platform for publishing accurate, AI-ready docs sites, with Git sync and an MCP server for AI tools.
AI tool for engineering teams that automates code review, status updates, and answers questions about what's changing in code.
Open-source asset-based data orchestrator, with Dagster+ cloud, for building, observing and delivering reliable data and AI pipelines.
No public pricing
No public pricing
Free trial available
No public pricing
Free trial available
- ✦AI-augmented development with human QA review
- ✦Agentic AI and workflow automation (including n8n)
- ✦AI application development and modernization/migration
- ✦Data analytics and AI insights
- ✦Chrome Enterprise, ChromeOS, and Google Cloud services
- ✦Zoom integration and migration services
- ✦Publish structured documentation sites
- ✦Git sync for docs-as-code workflows
- ✦AI setup agent to build and import docs
- ✦GitBook MCP server for AI access
- ✦Enterprise controls
- ✦Free tier to start
- ✦AI code review
- ✦Automatic engineering status updates
- ✦Agent that answers questions and takes action
- ✦Metrics on coding time and project focus
- ✦Pushed vs landed tracking
- ✦Commit and contributor insights
- ✦Asset-based pipeline orchestration
- ✦Built-in lineage and data-quality checks
- ✦Data catalog with asset metadata
- ✦Native dbt, Snowflake and Fivetran integrations
- ✦Branch deployments and hybrid deployment
- ✦Open-source core plus managed Dagster+ cloud
- →Build custom AI software with an offshore team
- →Automate business workflows with AI agents
- →Modernize legacy systems to the cloud
- →Migrate to ChromeOS or Zoom
- →Build data pipelines and dashboards
- →Publish product and API documentation
- →Maintain docs-as-code with Git sync
- →Make docs consumable by AI assistants
- →Import existing docs into a hosted site
- →Automating code reviews
- →Keeping stakeholders updated on engineering progress
- →Understanding what's changing in a codebase
- →Tracking team productivity metrics
- →Orchestrate ETL/ELT and dbt pipelines
- →Monitor data health and lineage
- →Build AI/ML data pipelines
- →Run reliable, observable data platforms