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DaveKnowsAI

What we build, and what we have already found

This is what "more efficient, less manual work, more revenue" looks like in practice. Eight things we build for a business with invoices, stock and suppliers to deal with, then eight faults we have found and fixed, with the real figures attached.

1,843

payments taken across our products

Not one chargeback. Not one dispute.

4.4m

records ingested and reconciled

Into a live product, not a spreadsheet exercise.

20,000

pages on one product

Built, maintained and monitored in-house.

What that looks like over time

Real figures from products we built, own and run. Anonymised, and shown as percentage growth rather than in pounds.

Visitors from Google, first four months of one product

From nothing to a live channel without spending on ads.

+37,429%
over the period
0%+10,000%+20,000%+30,000%+40,000%+37,429%Month 1Month 2Month 3Month 4Month 1: 0% since the startMonth 2: +2,571% since the startMonth 3: +13,543% since the startMonth 4: +37,429% since the start

Search Console clicks for one of our own products, in its first four months. No advertising spend.

What we would build for a business like yours

In the order most owners care about it. Money first, marketing last.

1

Invoicing, debt chasing and getting paid

Invoices raised from the job, sent when they are due and chased on a schedule that runs whether or not anyone remembers.

2

Reconciliation and finance processes

Bank, sales and suppliers lined up automatically, so a person only looks at the handful of lines that disagree.

3

Supplier cost control

A record of what you actually used, checked against what you were actually charged. Example B is what its absence costs.

4

Quotes and orders

One quote, priced from your own cost data, that becomes an order and then an invoice without being typed twice.

5

Stock, assets and equipment on hire

What you own, where it is, who has it, when it is due back and what it has earned while out.

6

Scheduling, calendars and jobs

Who is where tomorrow, what they need with them, and changes that reach the people affected.

7

Reporting you can actually trust

Numbers that trace back to the records behind them. Most reporting problems are counting problems, not chart problems.

8

Websites, and being found by AI

A site that does a job, plus ranking in search and being cited by ChatGPT, Perplexity, Copilot and Gemini.

Eight worked examples

Every fault below was found and fixed in systems we build, own and run, which is why the exact figures can be printed at all. Each one is a counting or control failure that gets more expensive with scale, because a bigger operation runs longer before anyone notices.

A

The step everyone was optimising already worked. The one in front of it was losing the customers.

2%of interested customers ever reached the point of paying

Of those reaching the payment step, 87% paid, out of a sample of 15. The rate was never the problem: the form in front demanded ten fields before it would show a price. Cut to five, price first.

Where this sits in a larger business

A tender win rate counted only on enquiries that survived a four-page form.

B

A supplier was being paid for 53% more than the work required, and every invoice was correct.

53%more units bought than the work required

624 units charged against 407 real jobs, because two parts of the same process each ordered the work. Nothing compared what was bought against what was delivered, so no control aimed at the supplier could have caught it. Residual after the fix: one duplicate in 1,006.

Where this sits in a larger business

Double-ordered stock, correctly supplied and invoiced. Plant left on hire after it came back to the yard.

C

Three counting errors, each invisible on its own, made every revenue figure wrong.

43%understatement in one trading entity, from one of the three

One payment account billed three businesses, so the same money was counted twice; income landed under two transaction types, and filtering on one understated two of them by 43% and 30%; and 112 test records counted as real sales. All three corrected.

Where this sits in a larger business

One merchant facility across several trading names; intercompany transfers counted at both ends.

Five more, same pattern

A number nothing was checking, or a check that could not tell failure from a quiet day.

D

The daily report said everything was fine. It had been recording nothing for eighteen days.

18 daysof total failure that reported as a normal quiet spell

A connection quietly expired, and every layer beneath returned an empty list rather than an error, so an outage and a quiet day produced an identical report every morning. The repair exposed three further faults of the same shape, including a currency conversion falling back to a rate of 1.

Where this sits in a larger business

Any feed trusted because it has always arrived.

The lesson, and it applies to any business

A check that reports nothing found when it fails is indistinguishable from success. Monitor that it ran, not only what it returned.

E

One customer queried one figure. The affected population was 1,075 documents.

1,075documents in the affected population, found from one query

A cost was estimated from an approximation while the authoritative figure was already being fetched and discarded, so two parts of the same document disagreed. Because documents were links rather than attachments, one fix corrected every past one.

Where this sits in a larger business

Any document mixing live data with a stored assumption: quotes, schedules, valuations.

F

A live system was giving its paid product away, because two safety checks inferred a test environment.

2 of 2guards that concluded the live site was a test machine

Both were written as: if the API key is missing, this must be a developer machine. Production had no keys configured, so both agreed, and the paid product went to anyone holding the right link.

Where this sits in a larger business

Approval limits that pass when the approver field is empty. Access that defaults to allow when the directory is down.

The lesson

Never treat a missing credential or limit as evidence of anything except a missing credential or limit. Absent must fail closed.

G

2,481 referrals from a promotion. Exactly one of them was a person.

1 in 2,481referrals that came from a human being

A promotion across thousands of pages appeared to be sending traffic; two independent measurements agreed almost all was automated. What separated people from bots was time on the page, not the bounce rate everyone looks at. It stopped a project about to be built on the number.

Where this sits in a larger business

Any metric about to justify a spend that nobody has tested for realness.

H

Being recommended by AI assistants is a separate discipline from ranking on Google, and it can be worked out.

268 vs 4AI visits to the well-structured page against the better-ranked one

Two pages on one site: the better-ranked draws 4 visits from AI assistants on around 10,000 Bing impressions; the other has a sixth of that visibility and draws 268, up from 85. Ranking and domain strength cannot explain it, because both share them.

Where this sits in a larger business

Buyers asking an assistant to shortlist suppliers in your sector before running a search.

Status: shipped and being measured, not yet proven

The 34-page rollout is live and tracked. It has not yet produced a proven result, and we will not claim it worked until it has.

If any of that sounded familiar

The first conversation costs nothing. We use it to work out whether there is anything here worth doing, and if there is not, we will tell you.

Or email us directly: dave@daveknowsai.com