We aim to democratize Artificial Intelligence
We aim to democratize the most important technological breakthrough in human history, technology of intelligence. Evolutionary increase of intelligence in homo sapiens changed the world. Increased intelligence in machines can trigger a step change of similar proportions and we aim to be the platform for companies to lead that change.
How are we achieving this?
Industry analysts help companies understand complex B2B solutions. However, the industry is opaque, opinion-based and expensive to use. We aim to change that. We are the AI industry analyst that provides data driven insights based on transparent metrics freely to enterprises.
We are building a transparent marketplace of companies offering B2B AI services. We use transparent criteria like reviews, website visitors, the number of times a company is searched on Google, their number of employees etc. With these transparent criteria, we allow companies to look beyond marketing speak, beyond huge marketing budgets to understand how they can use AI in their businesses and evaluate AI products and services objectively.
We are not just observers. We conduct our own research, challenge vendors, talk to users and, when possible, use the products & services ourselves to understand their value.
Our users have little time to discover new tech solutions and solve their problems. We will not waste your time with unnecessary verbiage. We uncover insights and share them in the simplest manner possible.
Knowledge is meant to be free. An additional enterprise that benefits from our research brings us almost no additional cost. It should also not bring them no additional cost.
Why do we do this?
B2B tech procurement is broken. Cem Dilmegani founded AIMultiple after a decade of advising Fortune 500 in using technology for improving performance. Working both as a consultant and as a tech buyer, he saw that he could either get raw data on vendor popularity and performance or opaquely prepared views of analysts’ assessments of vendors. Getting the raw data and aggregating it was time consuming and relying on opaque data was not his thing.
Working with AI companies, he also had the chance to see their side of the experience. They spend long hours explaining their solutions to analysts with little to show for. They need to work with review aggregator sites where companies’ fates are decided by people who are trying to spend as little time as possible while filling out a review so they can get their free coffee for the review and move on.
So he set out to use all available data on tech vendor performance, with a focus on AI, to formulate a transparent analysis of vendor performance that requires no additional effort from tech companies. They just need to get more customers and we observe the results in terms of their improved features, increased traffic, team size and reviews. Yeah, we couldn’t abolish the fact that coffee-for-review model is still an important factor but at least we help tech companies get more recognition just by registering with us in a few minutes and building their business.
How did we get here?
As any entrepreneur would admit, it was/is not an easy path. In the first year of AIMultiple, we tried hundreds of initiatives such as newsletters to share our analysis. Two of those initiatives, well written research articles and transparent vendor lists, worked and we stuck with them. We are now a global, remote team focused on helping firms find AI solutions.
Why are we called AIMultiple?
Financial metrics such as net income and EBITDA developed during 20th century have been used to value companies. In the future, a tech company’s AI capabilities (its unique data, capability of its workforce, systems, network of suppliers and culture) will be determining that company’s value. We help companies build their AI capabilities so they can take advantage of AI and multiply their value.
Are we truly, absolutely, 100% objective?
No. No company is. All industry analysts from Forrester to Gartner, earn revenues both from the companies whose products they cover or from the companies whose tech procurement decisions they support. So do we.
We are building the most objective industry analyst and we are aware that
- there is no such thing as 100% objectivity. We need to constantly look for ways to improve our objectivity and remove bias from our work.
- Existing industry analysts have not tackled this problem effectively
- Objectivity fosters trust and it is crucial for the future of our business to be the most objective industry analyst
Acknowledging the inherent conflicts within our business allows us to build mechanisms to manage them.
What are the concrete steps we are taking to make our work more objective?
We don’t think we will ever be 100% objective but we are taking steps to further reduce the bias in our content.
Bulding vendor lists based completely on transparent metrics
Vendor lists are the most vulnerable pieces of content for an industry analyst. There will always be pressure from customers to rank higher. In our vendor listings on aimultiple.com, we completely rely on data for ranking. There is no place for opinion in those lists. We clearly identify the sources of our data in our vendor lists.
Creating awareness about the conflicts that we face
Highlighting the conflicts inherent to our business helps us build mechanisms to manage it. For example, our research articles include more speculation than our vendor lists, it is not possible to predict future of an industry in an objective way. We are inevitably biased by our interactions with vendors and tech buyers when we make predictions. We are aware of this and it is the nature of our work. We maintain the highest level of professional standards and try to clearly explain the rationale behind our predictions.
Relying on advisors to validate our findings
We spend our days with research and conversations with tech buyers and vendors which creates bias in our research. We are starting to work with advisors that are:
- Only concerned with the objectivity and accuracy of the content that they review. They will not be financially compensated by us which limits our influence on them. They will also not be affiliated with any technology provider
- They will know the topic they are reviewing well. For more commercially focused topics, we will work with experts with more than 10 years of experience in a leading companies. For more academic topics, we will work with computer science PhDs with industry experience or professors.
Will experts be 100% objective? No. Their experience in the specific companies that they worked in and the tools they used can lead to bias. However, this is just a fact of working with experts and they will not have any financial motivation to be biased.
We are seeking out experts who can help us create more objective articles. Feel free to reach out to us at if you have more than 10 years of industry experience or a PhD in a related field, are not affiliated with any technology solution provider and are willing to support us by reviewing our articles in your field without any compensation other than more visibility for your personal brand.
Reach out to us at [email protected]. We help companies to find the right AI solutions and AI companies to improve their products and communication.