The infrastructure behind AI-native timelines.
Three internal accelerator frameworks we build with on every engagement, so we can move fast without compromising security or control: sandboxed execution, guardrails, and full workflow observability. These are how we deliver, not products we sell.
Secure agent & coding harness
The framework we use to run frontier coding agents like Claude Code inside a sandboxed, isolated environment, keeping data in place and every action on an audit trail.
For: Engineering teams with strict data controls
Key capabilities
- Sandboxed, isolated execution environment
- Multi-model: switch providers without re-plumbing
- Full audit trail of prompts, outputs and code changes
- Guardrails and observability built in
Internal AI app builder
An accelerator for standing up internal tools and workflows fast: describe the app, and we generate and deploy it with enterprise controls and governance in place.
For: Ops and analyst teams without dedicated engineers
Key capabilities
- Natural-language app and workflow scaffolding
- Data models, workflows and UI generated from a description
- Connect systems without manual integration work
- Deploy to managed, monitored infrastructure
Operational context graph
Connects systems, metrics and dependencies into one navigable graph that agents and dashboards can reason over: the shared context layer behind our ops and finance work.
For: Ops and finance teams that need one source of truth
Key capabilities
- Context graph of systems, metrics and relationships
- Live dashboards in place of manual reporting
- Actuals flow automatically into forecasts
- Anomaly detection before issues compound
Want these accelerators in your stack?
Book a discovery call and we'll show you Forge, Studio and Atlas running on a real workflow.