Our Story

We Came To AI From The Outcome Side.

We didn't come from a research lab or a software company. We came from inside sales, marketing, and customer success teams. Where technology is only valuable if it drives outcomes.

For over a decade, we saw the same pattern repeat:
The software worked. The business didn't. 

CoverageAI was built to change that.

Technology has never been the problem. Execution has.

70%

of enterprise AI deployments fail to deliver measurable business impact. Not because the technology is broken. Because it was never really inside the business.

Enterprise history is full of expensive technology failures, not because the platforms were broken, but because implementation failed.

In 1999, Hershey's invested $112 million in an SAP transformation. The system went live just before Halloween, their busiest season. It couldn't process nearly $100 million in customer orders, contributing to a 12% drop in the company's stock price.

Nike's rushed demand-planning rollout disrupted its supply chain so severely that it contributed to approximately $500 million in lost market value. The software functioned. The implementation did not.

Revlon. MillerCoors. National Grid. Lidl.

Different industries. Different technologies. The same outcome.  
Technology was deployed. Execution was missing.

AI is repeating the same story

Today's AI wave looks remarkably familiar.

RAND Corporation found that more than 80% of AI initiatives fail, roughly twice the failure rate of traditional IT projects.

BCG reported that 74% of organisations struggle to generate measurable value from AI investments.

MIT's Project NANDA found that only 5% of AI deployments produced meaningful revenue impact.

McKinsey's latest global research shows that while AI adoption has become widespread, only a minority of organisations report measurable bottom-line impact.

Different researchers.Different datasets.One conclusion.

Deploying AI is easy. Making AI deliver outcomes is hard.

The difference isn't better AI.

It's better execution.

The best organisations redesign the business around it. Workflows change. Ownership changes. Operating models change. AI becomes infrastructure, not software. That's the gap CoverageAI was built to close.

Different researchers.Different datasets.One conclusion.

The Broken Model

Before anything else

The outcome is signed

We agree on the number that matters. Not scope, not features, the business result you're accountable for.

FDE enters your organisation

In your Slack. Your daily stand ups. Your systems. Not clicking, embedded. Learning what no documentation could tell us.

Context mapping

Reality is absorbed

Edge cases, real workflows, unwritten rules, data quality, org politics. All of it. Before a single model is trained.

Build loop begins

Build → deploy → observe → fix

Every gap caught in the field is closed in the field. The AI learns the same way a new hire does, by living it.

Continuous

Iteration never stops until
the number moves

Unlike a handover model, nothing is signed off and shelved. The FDE owns the outcome, not the delivery.

Palantir popularised the concept of the Forward Deployed Engineers, technical experts embedded inside customer organizations, responsible not just for deploying software, but for making it create measurable business value.

That idea reshaped enterprise technology.

It reshaped ours too.

We embed before we automate.

Before we build, we learn.

Not the process on paper.

The process in practice.

The exceptions, shortcuts, and institutional knowledge that keep the business moving. Because AI succeeds only when it's built around the way work actually happens.

Then we stay.

Deployment isn't our exit. It's our starting point. We stay embedded until the outcomes we're responsible for are delivered and measurable.

We built what we couldn't
find. CoverageAI.

After years of stitching together disconnected AI tools, custom integrations, automation platforms, and workflows, we realized something.

The market didn't need another AI platform.

It needed one designed around operational reality.

CoverageAI combines business context, workflow intelligence, and execution into a single operating layer. Helping organizations move from experimentation to measurable business outcomes.

Instead of asking your teams to adapt to software, CoverageAI adapts to your business.

Take a Quick Look Inside the Platform

Our compliance and Certifications

AI for Banking

Coordinate self-service and agent support with shared context, consistency, and built-in compliance.

AI for Banking

Coordinate self-service and agent support with shared context, consistency, and built-in compliance.

AI for Banking

Coordinate self-service and agent support with shared context, consistency, and built-in compliance.

We Came To AI From The Outcome Side.

Technology has never been the problem. Execution has.

AI is repeating the same story

The difference isn't better AI.

The Broken Model