KeenDigit · Enterprise AI delivery team

How the team is organized

One team per layer of the stack we own.

The team mirrors the architecture: a practice for the AI product, one for the systems and data beneath it, and one for the controls and operations that sustain it.

Layer 01 · Product

AI-Native practice

Grounding, evaluation, guardrails, and human review for production AI.

Layer 02 · Substrate

Foundations practice

APIs, databases, and legacy modernization — the AI-ready substrate.

Layer 03 · Bedrock

Run & Assure practice

Infrastructure and independent security audit. Vendor-neutral.

The practice leads

The people you'll actually work with.

Three senior leads cover the connected layers of enterprise AI delivery, with named responsibility throughout the engagement.

  
  AI-Native lead 
Michael Brennan
Principal, AI Engineering
Production AI — grounding, evals, and the kind of systems they've shipped.
 LLM appsEvalsGuardrails 
  
  Foundations lead 
Kevin Zhao
Lead Engineer, Platform
APIs, data, and legacy modernization experience.
 APIsPostgreSQLSymfony / Vue 
  
  Assurance lead 
Simone Carter
Security & Audit Lead
Infrastructure, security audits, and vendor review.
 AuditLinuxVendor review 

How we work

Named responsibility, shared context.

The people making delivery decisions stay close to the workflow, system constraints, and approval questions across the engagement.

You meet who does the work

No bait-and-switch. The senior who scopes it delivers it.

Independent & vendor-neutral

We audit third parties without conflict — including ones you already use.

You keep control

Documentation, credentials, and code stay yours. No lock-in by design.

Named delivery leads

You know who owns the architecture, delivery decisions, and assurance work.

Direct working communication

Technical and operating questions reach the people responsible for the work.

Accountable to the scope

Every engagement starts with a written, agreed scope. The person who signs it is the person you can hold to it.

Built to hand back

We work so you're never dependent on us. Structured handover means the docs, credentials, and code are always yours to take elsewhere.

Start with the workflow

Bring business, technology,
and risk into one conversation.

Tell us what the AI system needs to change, what it must connect to, and what your organization must be able to approve and operate.

Discuss your AI project Why teams choose us

You meet who does the work Named delivery responsibility Rawlins, Wyoming · USA

Senior practitioners acrossthe production AI stack.