Run upgrade campaigns across dozens of repositories.
Control Plane for Coding Agents
Run coding agents safely at scale
Turn tasks into isolated, reviewable workflows. Every step gets its own container, git worktree, commit, logs, traces, and approval trail.
Works with Claude Code, Codex CLI, and custom CLI-based agent tooling.
Dependency upgradesFramework migrationsSecurity remediationRepetitive backlog executionMulti-repo refactors
Execution Model Preview
Isolation Container + Worktree
Output Commit + Trace
Control Checkpoint + Approval
The Problem
AI coding tools are powerful. Operating them safely across teams is still messy.
One engineer using one agent is manageable.
Dozens of concurrent AI tasks across repos, tools, and environments is where things break.
Black-box runs
Branch and workspace collisions
No replay or checkpointing
Weak audit trails
No policy guardrails
Too much vendor lock-in
What Noldarim Does
Noldarim turns a task into a DAG of isolated execution steps.
Each step gets its own boundary, history, and telemetry, so your team can run AI work in parallel without losing visibility or control.
That means you can safely coordinate upgrades, migrations, remediation work, and long-running agent workflows without collapsing into hidden state or workspace chaos.
Its own container
Its own git worktree
Its own commit history
Its own traces and logs
Its own checkpoint in a durable workflow
Best-Fit Use Cases
Best when AI work needs parallelism, review, and governance.
Execute codemods and migrations with approval gates.
Turn repetitive tickets into reviewable pull requests.
Automate remediation and cleanup work without giving up governance.
Coordinate long-running AI workflows with replay, retry, and traceability built in.
Why Teams Buy
Operational defaults that make agent execution manageable.
Isolated by default
Parallel by default
Git-native by default
Replayable by default
Auditable by default
Vendor-neutral by default
Security
Built for teams that need more than a chat window.
Self-hosted or controlled deployment options
Bring-your-own-model/API keys
Human approval gates for risky actions
Full execution logs and lineage
Policy guardrails for tools, environments, and actions
Why Not Just Use Agents Directly?
Direct tools are fine for solo work. Team-scale execution is a different problem.
Use agents directly when
- One person driving one task
- Ad hoc exploration or debugging
- Short-lived work without team coordination
- Minimal governance requirements
Use Noldarim when your team needs
- Multi-step workflow orchestration
- Isolation between steps
- Reviewable outputs
- Replay and rollback
- Cross-tool execution
- Team-scale governance
Final CTA