Field notes on building a company-owned AI operating layer: connected systems, reviewable skills, model choice, deployment control, and the forward-deployed work that makes it useful.
Two weeks ago, the open-source agent stack was missing a credible in-your-environment sandbox. With Tencent's CubeSandbox release, the gap is closed — and customer-controlled finance AI just became a much shorter procurement conversation.
SunSystems is exactly the kind of system where agentic finance workflows pay off — a stable, structured ledger sitting underneath brittle, swivel-chair processes. Here is the pattern we use to layer agents on top of it without breaking anything.
Xero is the cloud ledger most growth-stage CFOs and project-led businesses actually run on. The pattern we use to layer agents on top — for cash, runway, and margin answers in minutes, and live budget variance across a portfolio of projects — without ever owning the keys.
An open-weights model that is competitive with the closed frontier on agentic coding is exactly the event LLM-agnostic, customer-controlled architectures were designed for. Here is what it means for finance buyers — and the honest caveats that come with it.
If your agent can read the warehouse, the right question is not 'can it answer the question?' but 'what is the worst query it could run, and what stops it?' A practical model for thinking about LLM-generated SQL in finance environments.
Most AI tools ask finance leaders to give up the data, the model, and the deployment posture in one go. There is another way.
A skill is a versioned, reviewable definition of how your team runs a recurring finance process — authored with you, not handed to you in a docs link.
VPC and on-prem are not exotic any more. Here is what a phased deployment actually looks like for a finance function with real residency, regulator, and audit constraints.
Routing per task — not per platform — is how you keep the cost curve, the capability curve, and the procurement story under your control.
Ledger reality, pipeline reality, and ops reality each live in their own silo. The disconnect between them is what breaks your reporting — across finance, sales, and operations.
MLX runs inside your environment, against your systems, with the model you choose. Map your highest-value workflow and start with read-only analysis.
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