Data Transparency Our AI results are evidence-based

In an enterprise artificial intelligence market saturated with inflated promises, we choose the opposite path: to show the source behind every data point. The tables on this page collect the sources behind all of our stat cards, every figure our source audit changed, and the figures linked in our Pulse articles (in Spanish), each with a link to the original study. This is what we mean by transparency: verifiable data, citable benchmarks and zero unfounded guarantees.

Trust is not declared, it is demonstrated. Most B2B AI vendors publish results figures without saying where they come from, and many of those figures do not hold up to verification. We prefer to expose our sources so you can judge the strength of each claim on your own terms.

This page serves two functions. For you as a client or evaluator, it is the proof that our marketing claims have real backing: studies from consultancies, independent analysts and academic papers, and vendor data labeled as such. For us, it is an internal commitment: no number goes on the site without a source to back it, and this page brings those sources together in one place.

Not all numbers mean the same thing, and part of being transparent is explaining what kind of data you are reading in each case. That is why we classify each numerical claim into one of three categories, and we identify it in the "Type" column of each table:

Industry benchmark. This is a data point that comes from independent research: consultancies such as McKinsey, Bain or Deloitte, analysts such as Gartner or Forrester, peer-reviewed academic papers, industry associations, public and standards bodies (regulators, central banks, official statistics, standards organizations) and reference reports for the sector. When we say "industry studies show that...", we are in this category. It represents the industry average or range, not a result we guarantee to you. It is the kind of source we prioritize.

Vendor data. Some relevant figures are published only by companies that sell the solution the data describes. We include them because they provide useful reference when no equivalent independent source exists, or as a reference next to one, but we always label them as such, because they come from an interested party and may be subject to selection bias. This category also covers what each company publishes about itself or its product, such as its number of customers, its list prices or its API limits. Whenever an equivalent independent source exists, we prioritize it over the vendor's.

Improvement documented in our own cases. When we publish a number as a Vantegrate result of our own, it is because it is measured in real production with a client who agreed to be a case study. These cases are always identified as such and are never presented as a general industry benchmark.

Apart from those three categories are the figures we give about ourselves: how many integrations we have, the team's track record and how fast we reply. They are in the first table on this page, marked as our own figure, with what each one means and what it does not.

These tables collect, by topic, the sources behind every stat card on the site, every figure our source audit changed, and the figures linked in our Pulse articles (in Spanish). Each row shows the claim, the figure, a link to the original source (with its year when the source states it) and the type of data. Some figures in the body of integration pages and Pulse articles link to their source in the same paragraph and do not have their own row here.

Some of the numbers above come from companies that sell the solution the data describes. We include them because they provide useful reference, but we always mark them as "vendor data" so you know they come from an interested party and may be subject to selection bias. When an independent source exists (consultancy, analyst, paper, industry association), we always prioritize it over the vendor's.

Most available benchmarks are global or centered on the United States. Data specific to enterprise artificial intelligence in LATAM (Argentina, Mexico, Brazil, Chile, Colombia and Peru) is still scarce in analyst literature. When we use a regional data point (for example, WhatsApp Business cases in the region), we flag it explicitly. In the remaining cases, absolute values may differ by country, and it is best to take them as directional reference, not as an exact figure for your market.

Where do the numbers Vantegrate shows on its site come from?

Every results figure comes from one of three sources: an independent research benchmark (consultancies, analysts, papers), a figure published by an industry vendor (labeled as such), or our own case measured in production with a real client. The sources for our stat cards and page figures are in the tables on this page, each with its link; a figure inside body text links to its source right there.

Does Vantegrate guarantee these results for my company?

No. Benchmarks describe the industry average or range according to industry studies, not a guaranteed result. Actual results depend on the implementation, the quality of the data and the adoption of each organization. We explain this in detail in the disclaimer at the bottom of this page.

What is the difference between an industry benchmark and vendor data?

An industry benchmark comes from an independent source with no commercial interest in the result (for example, a McKinsey study, an academic paper or a public or standards body). Vendor data comes from a company that sells the solution the data describes, so it may be biased; we include it when there is no equivalent independent source, or as a reference next to one, and we always label it.

How often are the sources updated?

We review and refresh the sources periodically, and we correct any figure that becomes outdated relative to the latest research. The time anchor is in each source, not in a stamp at the bottom: the table links the original study, with its publication year when the source states it. That tells you how current the number is, which is the real question. If you see a figure that has gone stale, write to us and we will fix it.

What happens if a number does not have a solid source?

We do not publish it as a number. We replace it with a qualitative description, such as "significant and consistent improvement." We prefer to communicate less than to claim something we cannot back with evidence.

Why does Vantegrate publish a data transparency page?

Because trust is demonstrated with verifiable evidence, not with statements. It is our way of standing out in an enterprise AI market full of unsupported figures, and an internal commitment not to communicate any number we cannot document.

The benchmarks on this page describe the average or range of each industry according to the research available at the time of publication. They are informational and for reference purposes.

None of the figures presented here constitutes a guarantee of result. Vantegrate does not guarantee that your organization will obtain the same numbers, or equivalent results, simply by adopting our tools. The benchmarks reflect what other organizations in the sector have reported, not what you will achieve.

Actual results vary from one company to another and depend on factors that are outside Vantegrate's control. Among them: the degree of responsibility and rigor each organization brings to implementing its processes, the correct configuration and use of the tools, the quality and cleanliness of the data available, the level of commitment and adoption from users, and the particularities of each company's operational, regulatory and market context. A partial implementation, low internal adoption or poorly defined processes can produce results substantially different from the reference benchmarks.

The content of this page also does not constitute legal, financial, regulatory or professional advice of any kind. For decisions that depend on these benchmarks, consult with qualified advisors in your jurisdiction.