ColdVault Code

Stage: In development

Deterministic governance for AI-generated code — prompt-based rules are suggestions; code-enforced rules are walls.

Built-in governance

Requirements must exist and be confirmed before code is written. The tool refuses to commit without a requirement reference — not as a prompt instruction the agent can ignore, but as code that literally will not execute.

Multi-model code review

Every change reviewed by a panel of 6–9 AI models against the requirement. Our benchmark shows each model finds unique critical defects others miss — a safety net no single model replicates.

Multi-model code generation

For critical tasks: two architecturally different models generate independently, a third synthesises the best output. Fewer regressions than single-model generation; marginal overhead next to review cost.

Encrypted infrastructure

Optional zero-knowledge mode via ColdVault on Confidential VMs. Your source code never leaves encrypted memory. For teams where the codebase itself is sensitive IP.

Express interest

Built-in governance

Requirements must exist and be confirmed before any code is written. The tool refuses to commit without a requirement reference — not as a prompt instruction the agent can ignore, but as code that literally will not execute. Blast-radius limits cap every commit; the agent cannot bypass what it cannot control.

Multi-model code review

Every change is reviewed by a panel of 6–9 AI models checking the diff against the requirement. According to our ColdVault Benchmark, each model in the panel identifies unique critical defects the others miss — creating a safety net no single model can replicate.

Multi-model code generation

For critical tasks, two architecturally different models generate code from the same prompt independently. A third model reviews both outputs and synthesises the best implementation — or generates from scratch if neither meets the bar. In our experience this produces fewer regressions than single-model generation. The overhead is marginal compared to the review cost that happens regardless.

Encrypted infrastructure

Optional zero-knowledge mode via ColdVault on Confidential VMs (AMD SEV-SNP). Your code never leaves encrypted memory. For teams where source code is sensitive — regulated industries, proprietary algorithms, competitive IP.

See: Why we built this

For our own internal development, we use multi-model code review and generation daily across multiple repositories. We started by adding requirements checking, review panels, commit limits, and audit trails on top of an existing AI coding tool. It helped — but agents consistently found paths around every rule we added. They optimise for task completion; process feels like friction to an optimiser. Client-side hooks are negotiable when the agent controls the terminal.

We moved enforcement from the prompt layer into the execution layer. ColdVault Code does not suggest rules — it enforces them. Requirements are checked programmatically. Reviews are mandatory and cannot be dismissed. Scope is verified against the original request. The result: changes that match what was actually asked for, without the babysitting.

The same orchestration engine powers TestRobin and RunRobin — the underlying platform for autonomous task execution is shared across our automation products.

See: Modes

Fast. Single model, lightweight tasks — doc updates, simple fixes, config changes. Cost-effective.

Standard. Single model generation with multi-model review panel. Default for most work.

Deep. Multi-model parallel generation + synthesis + full review panel. For critical code where getting it right the first time matters more than cost. Two models generate independently, a third synthesises, then 6–9 models review against the requirement.