hhelpmybiz
Already tried AI?

Your AI costs more than it saves?
We can review it and fix that.

Most AI tools underdeliver not because the technology is bad — but because of how they were set up. We find the real cause and fix it, often without starting over.

74%
of deployed AI chatbots had to be rolled back or shut down after failures
67%
of customers abandon the conversation when a bot traps them with no way out
1 in 5
people see no benefit at all from AI customer service — 4× the failure rate of AI overall

What usually goes wrong — and what fixes it

The failure patterns we see most often, with what actually causes them and the result when they're fixed properly.

The problem

Confidently wrong answers

The bot was left to “know everything” instead of being grounded in your real data, so it invents plausible-sounding answers to fill the gaps.

Real case: A UK bank chatbot gave 140,000 customers incorrect overdraft-fee info because it ran on outdated policy data.
How we fix it

 

We ground every answer in your current documents and make it cite the source.

22%of AI failures are these "hallucinations" — eliminated by grounding
The problem

No clean handoff to a human

It was deployed as a wall between the customer and your team, with no escape hatch — so people feel trapped and give up.

Real case: Air Canada's bot promised a refund that didn't exist in policy; a tribunal forced them to honor it.
How we fix it

 

We let it handle the routine and escalate to a human with full context the moment it should.

67%of customers abandon a chat when stuck in a bot loop — fixed by smart escalation
The problem

Doesn't know your business

It runs on generic, out-of-the-box knowledge and never learned your products, prices, policies or tone.

Real case: Teams train a bot once on a static FAQ, call it done, then watch satisfaction scores fall for months.
How we fix it

 

We train it on your products, policies and real past tickets — and keep it updated.

<40%resolution rate signals broken training — proper grounding pushes it far higher
The problem

Disconnected from your tools

It sits in its own silo, unable to see your CRM, orders or inventory — so it can't actually do anything, and staff still copy data by hand.

Real case: In e-commerce the bot can't give real order status or return eligibility, so every useful query still hits a human.
How we fix it

 

We integrate it into your existing stack so it reads real data and acts end to end.

35%no-match rate dropped to 0% once a real setup connected the data (Zoom)
The problem

No way to tell if it helps

No goal and no measurement were ever set, so nobody can prove ROI — the single most common reason AI projects quietly fail.

Real case: Most teams deploy and stop watching, so the same failure points persist unseen for months.
How we fix it

 

We set a clear metric up front (resolution rate, time saved, response time) and track it weekly.

4×higher "no benefit" rate for AI support vs AI overall — measurement closes the gap
Our fix process

We audit what you have before rebuilding anything

Most of the time your existing AI can be salvaged. We find the real gap first, then fix the smallest thing that makes it work — you don't start over.
1

Audit

We review your current setup, data and prompts to find exactly where it breaks down.

2

Diagnose

We pinpoint the real cause — data, grounding, workflow or integration — and what it takes to fix.

3

Fix and measure

We fix the gap, connect it properly, and set a metric so you can see it working.

Let's get your AI actually working

Send us what you have. We'll run a free 30-minute audit, tell you honestly what's wrong, and give you a fixed quote to fix it — no obligation.

Book a free audit