<NESway/>Let's Build Together

AI Governance & Domain LLMs If you can't measure your AI, your CFO will cancel it.

Governance, ROI measurement and domain-tuned models that get AI past procurement, past the regulator and onto the P&L.

Let's Build Together
Hours saved
Value
Personal data
Risk
Needs controls
Needs controls
2 services in AI Governance & Domain LLMs. Point at one to see what it fixes.

Unmeasured AI gets defunded.Measured AI gets scaled.

AI budgets are now being audited from two sides. Finance wants evidence of return before releasing more spend. Regulators want evidence of control: the EU AI Act's high-risk obligations and transparency rules are already in force, with penalties up to 7% of global turnover. Meanwhile, IBM found 63% of breached organizations had no AI governance policy at all. Governance used to slow AI down. Now it's what keeps it funded.

7%
of global annual turnover: the maximum EU AI Act fineEU AI Act (Regulation 2024/1689) (opens in a new tab)

What changes for the business

  • Every AI system inventoried, risk-rated and owned
  • ROI tracked per use case, in numbers finance accepts
  • Models that speak your industry's language and respect its rules

2 ways in

Each one has its own page, and each page runs the work live. Open one and play with it.

  1. Responsible AI, AI governance & ROI measurementGovernance that speeds AI up instead of slowing it down.An AI inventory, risk framework, approval flow and ROI dashboard, aligned to the EU AI Act, NIST AI RMF and ISO 42001.Try a triage
  2. Domain-specific / vertical LLM solutionsA general model knows everything. Yours should know your business.Models tuned and grounded on your domain's vocabulary, documents and risk rules, for answers specialists actually trust.Try an assistant

What buyers ask first

Won't governance slow down our AI projects?

Heavy governance does. Ours is tiered: low-risk uses get a fast approval path, and controls scale with risk. Projects stop waiting on committees because the rules are clear before they start.

Should we fine-tune a model or use RAG?

Start with retrieval-augmented generation in most cases: it's cheaper, easier to update and cites its sources. Fine-tuning earns its place for consistent style, specialized formats, or when a smaller model must match a larger one's accuracy at lower cost.

Let's talk AI Governance & Domain LLMs.

One call with the senior engineer who would run it. You'll leave with a straight answer on what it would take.

Let's Build Together

Next practices along

22 practices in all. See every one