AI Consulting

AI that does more than generate.

We design AI systems that sell, support, research, create, remember and operate — then fit them into the way the business actually works.

The real problem

AI is easy to demo.
Reliability is harder.

A clever chatbot is not an operating system.

The hard questions are operational: what context must persist, what actions should be permitted, what still requires human judgment, what happens when confidence is low, and how the system connects to the rest of the business.

Try the systems

Don't just read about it.
Use it.

These are front-end demonstrations of three business functions. In production, each agent would have its own context, memory, tools and escalation logic.

AI Sales Agent

I reviewed what you're selling. Before I recommend anything: where does interest currently drop off?

AI Content Engine

Give me the campaign objective, audience and one thing the brand must never sound like.

AI Customer Service

Are you asking about an active Pulse project or evaluating us for a new one?

AI Sales Agent
I reviewed what you're selling. Before I recommend anything: where does interest currently drop off?
At the website.
Then I'd inspect the transition from promise → proof → action before recommending more traffic.
What we build

Systems, not features.

01

Agentic workflows

Research, lead handling, CRM updates, content operations and other multi-step work where the system needs to plan, act and verify.

02

Knowledge systems

Persistent context, retrieval, structured memory and internal decision support so useful information does not disappear into folders and chats.

03

Customer-facing AI

Sales, service, onboarding and personalized interaction designed around real escalation and trust boundaries.

04

Internal automation

Reduce repetitive work while preserving the human judgment that creates actual business value.

Our own system

The proposal journey is part of the proof.

Audit → AI scoping → fit check → proposal.

We are building the same kind of systems we sell. A prospect can experience context-aware scoping, adaptive questions and automated proposal generation before becoming a client.

What makes a system good

It knows when not to act.

Context

The system has the information needed to make the next decision without asking the user to repeat themselves.

Boundaries

It knows what it is allowed to do, what needs approval and when confidence is too low to continue autonomously.

Verification

Important actions are checked rather than assumed successful.

Escalation

Human involvement is designed into the workflow instead of treated as failure.