We use a proprietary selection process which is dynamically refined and takes inputs from legal professionals, clients and our research.

Our research team uses an array of weighted variables and a high tech recursive self-improving artificial intelligence to find potential candidates. Our artificial intelligence (AI) named “BarristerBot™” allows us to process/interpret information that would otherwise take thousands of people to interpret.  Manually evaluating this information is like using an abacus (pre-calculator) to do math.

We assess results, honors, credentials, recognition, on millions of publications, legal records and articles online.

Initial candidate creation/evaluation

We start with a pool of initial candidates through nominations and from evaluations from our research department.

This initial list is then scrubbed and some candidates are immediately eliminated who flag certain variables (for example, they are not licensed/practicing lawyer).
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Weighted Evaluation

Our panel then evaluates each and every candidate on a 1 to 10 scale. This panel is mainly constructed of legal professional but also takes input from other members

and our AI BarristerBot™. Candidates scores are added up and no more than 2% of total lawyers in our country become members.
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Subsequent Cycles

Evaluation occurs annually and independently each year. We are not stagnant and continue to refine and improve our selection process. Being recognized one year

does not mean someone will be selected in subsequent years to follow.
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