LLM Governance Consulting

LLM governance consulting is the work of putting owners, intended-use rules, runtime controls, reconstructable traces, and eval gates around enterprise language models. It is not a slide deck of principles. We implement the register and the control path in your cloud, under a zero-retention, SOC 2-aligned process, with you owning the IP. Four weeks is standard for one bounded program; financial-services review typically takes 8–12 weeks.

At minimum: system name, business owner, technical owner, intended use, out-of-scope uses, data classes, model and vendor, tools the system can call, eval status, residual risk, and next review date. Shadow ChatGPT use belongs on the list too, even if the answer is “replace or ban.” An inventory you cannot query is not governance; it is a forgotten spreadsheet.

Ethics guidelines state values. LLM governance states who may use which model on which data, which tools it may call, how a decision is reconstructed, and what fails a release. Values without a trace store and a CI gate do not survive the first production incident. Consulting work is the latter: controls, logs, and owners, written so engineers can ship against them.

You need a thin version: intended use, data classes, a logging pattern, and a named owner. Waiting for a perfect framework is how shadow tools proliferate. We install a minimum register and trace path in four weeks, then thicken controls as the fleet grows. Financial-services clients usually fold this into an 8–12 week model-risk cycle.

A reconstructable trace stores the input, retrieved context, tool calls, model version, output, and any human override. That is how you prove a system stayed inside intended use, debug a bad action, and answer a second-line question without reconstructing from memory. Traces live in your cloud. We do not retain them. No shared training on your logs.

Golden sets, rubric judges, and CI gates are how you notice a prompt or model change that violates policy. Governance that only reviews documents at launch will miss drift. We treat eval failures as governance events: a groundedness drop is a control failure, not a product curiosity. The suite is yours at handover.

You do. Registers, policy packs, prompt and control configs, eval suites, and traces are client IP in your repositories. Work runs in the client cloud. Zero-retention means we do not keep your prompts or documents after the engagement. We are SOC 2-aligned and we do not train shared models on your data.

Four weeks is the standard implementation for one line of business: inventory, policy pack, logging pattern, first eval gate, handover. Heavier financial-services programs with second-line review typically take 8–12 weeks. After the first package, additional systems reuse the register and control pattern instead of starting a new committee.