Delta Mach Amp · AI Consulting

Most AI
Projects Fail
Before They
Start.

Not because the models are wrong.
Because the architecture was never designed to survive contact with a real organization.

The gap between an AI demo and an AI system that actually runs your business is an architectural problem.

We exist to close it.

Why AI projects collapse
MONTH 1 DEMO THAT DOESN'T SHIP MODEL-FIRST THINKING × vendor lock-in × data debt × team turnover × scale failure THE GAP WORKFLOW MAPPED ARCH VALIDATED FIXED-FEE POC PRODUCTION ARCHITECTURE-FIRST NOW 18 MONTHS
The problem with AI consulting today

Most Firms
Sell Outputs.
We Sell
Outcomes.

A strategy deck. A proof-of-concept. A fine-tuned model. None of that answers the question your CTO is actually asking: will this still work in 18 months, at 10x the volume, with half the team who built it?


Our position

We don't start with models. We start with your operations — the workflows, the data, the decision points where AI either creates compounding leverage or quietly creates compounding debt. Architecture comes first because everything downstream depends on it.


What that means in practice

It means we'll tell you when not to build something. It means our proof-of-concepts are scoped to answer a real business question, not to sell you the next phase. It means the person who designs your system is the person who builds it.

Three companies came to us with the same surface-level problem — too much manual work — and left with three completely different systems, because the underlying operations, data maturity, and risk profiles were different. That's the point.

58% Resolution
time cut
Insurance · Agentic AI

Autonomous Claims Processing

An insurer cut claims resolution time by 58% — not by automating everything, but by precisely identifying the 40% of cases where automation was safe. The other 60% still routes to humans, with better context than before.

+6pt Gross
margin
Retail · Process Intelligence

AI-Driven Merchandise Planning

A retailer recovered 6 gross margin points — not by predicting demand better, but by redesigning how buying decisions get made. The model was secondary. The workflow redesign was the intervention.

70% Expert
escalations
eliminated
Manufacturing · Knowledge AI

Enterprise Knowledge Agent

A manufacturer eliminated 70% of expert escalations — not by replacing experts, but by making their knowledge queryable. The experts are still there. They're just not answering the same question for the fourteenth time.

How we think about AI systems
BUSINESS OUTCOMES margin · resolution time · decision quality · escalation rate WHERE WE START OPERATIONAL WORKFLOW process mapping · decision points · human-AI handoffs · leverage identification SYSTEM ARCHITECTURE agent design · data flow · failure modes · scalability · governance DATA INFRASTRUCTURE readiness assessment · pipelines · feature stores · quality monitoring MODEL / AI LAYER WHERE OTHERS START

We Are a
Small Firm
By Design.

Every engagement is led by a senior practitioner. We take fixed fees because it forces us to scope honestly. We are stack-agnostic because our loyalty is to your outcome, not to a vendor relationship.

Senior practitioners only

The person who scopes your project is the person who delivers it. No bait-and-switch, no junior handoff after the proposal.

Fixed fees, honest scoping

We take fixed-fee engagements because it forces us to define success before we start. No billable-hour ambiguity.

Stack-agnostic

We have no vendor relationships to protect. Our recommendation is whatever is right for your architecture, full stop.

We'll tell you when not to build

If the answer is don't build this yet, we'll say so. Our reputation depends on your outcome, not on selling the next phase.

Get started

We Take
Three New
Clients Per Quarter.

If that sounds like how you want to work, we should talk.

Book a Conversation →

hello@deltamachamp.com