- Where does our data go?
- MLX connects read-only to the systems you approve and keeps each target scoped to your organisation. Those source systems remain authoritative. When a workflow uses an external model provider, the context needed for that request follows the provider path configured for your deployment.
- Do we need to migrate our legacy systems first?
- No wholesale or rip-and-replace migration is required. A focused activation connects the priority systems you approve, starting read-only, and brings the relevant evidence into the Twin while those systems remain authoritative. Mercury Labs engineers then work with your experts to turn that evidence into governed business context — written down, tested and versioned.
- Can we choose models and control their cost?
- Yes. The governed business context stays separate from the model provider. You can use stronger models for demanding work, lower-cost models for routine tasks or evaluate another configured provider without rebuilding that context. Material changes are tested before rollout.
- What does this cost?
- MLX is a scoped engagement. Mercury Labs engineers support the activation and operate the configured target, while model usage is recorded where provider evidence is available. Talk to us for a proposal based on the systems, workflows and operating requirements in scope.
- Why not just use ChatGPT or Copilot?
- Use them where they fit. The Twin gives your AI tools the governed business context they normally lack, including agreed definitions, source freshness and evidence about what each answer used — and agents can file their work back into channels as auditable records. It complements the AI surface rather than replacing it.
- We're regulated. Can we actually use this?
- MLX starts scoped to your organisation and read-only, and business context ships as sealed releases you can review before they are activated. Normal governed queries do not include browser, terminal or write access. A regulated deployment still requires approval of the exact data and model paths, evidence retention and operating controls.
- What do the AI agents actually see?
- During the build, the authoring agents never read your rows. Sensitive values are converted to keyed fingerprints before anything is compared, and the agents work from descriptions and measurements — so relationships can be found without raw values reaching them. Once the Twin is live, agents work inside your organisation's permissions: they can pick the published, governed context or explore your connected records free-form.
- Which systems can you connect?
- Current connectors: Xero, SunSystems, Stripe, GoCardless, Microsoft 365 and SharePoint, Google Drive, Docs and Sheets, Gmail, Google Calendar, Outlook, Slack, Microsoft Teams, Granola, Notion, Linear and GitHub. Legacy ledgers such as Infor SunSystems stay queryable without migration; exact scope is confirmed before activation.
- What happens when the Twin cannot support a question?
- It says so. A governed answer identifies the published product, version and freshness it used. If that product does not support the requested question or evidence, the Twin returns 'not supported' instead of producing a plausible guess. Agents can still explore the underlying records free-form — that work is simply not labelled a governed answer.