05 · What we build

Build on solid ground.

A fast, honest audit of your data, systems, security and people, so you know what you can do now, what to fix first and what to leave alone.

What it is

AI projects rarely fail because the model was not smart enough. They fail because the data was scattered, the systems could not connect, nobody had decided what could go to which provider, or the team had no time to learn the new way of working.

A readiness check finds those problems before you pay for them. You get a plain scorecard and a sequenced list of fixes, plus a green-light list of things you can start on immediately.

In practice

What we look at, and what the research says

Data

Where it lives, how clean it is, how duplicated, who can access it. Data quality shows up near the top of the barriers leaders cite in industry surveys.

Systems

Which of your tools have APIs or exports, and what would break if something was connected.

Security and privacy

What information may go to which AI provider, how personal or health data is handled, and what the vendor terms actually say.

Governance

Who approves what, what gets logged, and what your team may and may not paste into a chat window. Deloitte found only 21 percent of enterprises report mature governance for agentic AI.

People

Skills, champions and time. Microsoft's 2026 Work Trend Index found organizational factors drive two thirds of reported AI impact.

What we build

What you get

  • A scorecard across data, systems, security, governance and people
  • A prioritized gap list, each item with an owner and a rough effort
  • A green-light list of AI uses that are safe to start now
  • A short acceptable-use policy your team can actually follow
  • Vendor and provider notes on data handling and terms
  • A recommended order of operations for the next 90 days
How it runs

A typical engagement

  1. InventoryWhat data, tools and accounts exist and where.
  2. TestSample data quality and check how systems can connect.
  3. Assess riskPrivacy, security and compliance questions answered plainly.
  4. ReportA scorecard, a fix list and a green-light list you can use immediately.

A good fit if

  • You are about to invest in AI and want to avoid surprises
  • You handle sensitive customer, financial or health data
  • A previous AI attempt stalled and no one knows why

Probably not a fit if

  • You have already done a thorough audit recently
  • You want certification or a formal legal opinion, which we are not
Questions

Common questions

Is this a security audit?

It is a practical review of AI-related security and privacy, not a penetration test or a formal certification. If you need one of those, we will say so and point you to the right specialists.

Do we need to fix everything first?

No. The green-light list exists so you can start with the safe, useful things while the harder fixes happen in parallel.

Can this lead into a build?

It can, and often does, because you leave with a clear order of work. There is no obligation to continue with us.

Want help with readiness checks?

Tell us what you are trying to fix. We will give you an honest read on whether this is the right move.

Just curious? coffee@aiveny.com

You have a question, a hunch, or an idea that is still half-formed. Write it however it comes out. No pitch, no pressure, no form to fill in.

Ready to build? tacos@aiveny.com

There is a real project, a deadline, or a process eating your week. Tell us what is going on and we will dig in with you.

Not sure which inbox? Pick either. They land in the same place.