OUR USE CASES

We build a team of annotators who annotate or tag data in the selected software of your choice. Our team is led by Data Scientists skilled in Odetta's Best Practices of Annotation. Annotation (also known as data labeling) is the process of tagging the data like text or objects in videos and images to make it detectable and recognizable to computer vision to train the AI models through machine learning algorithms. Examples include identifying spam documents, teaching computers how to read and write by scoring text documents for meaning, categorizing Net Promotor Surveys, performing facial recognition by tagging boundaries of digital faces, classiying images based on criterion such as style/season, editing images in photoshop, finding the parent company of a list of entities, categorizing entities based on pairing relationship within a schema. We have been told we are unique in the market for subjective annotation requiring higher level cognition.

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We build teams of MBAers trained in business concepts such that they can categorize business entities using several heuristics. Industry classification or industry taxonomy is a type of economic taxonomy that organizes companies into industrial groupings based on similar production processes, similar products, or similar behavior in financial markets. We often categorize companies by Business Model based on Heuristics. Business concepts include understanding how to categorize SaaS, SaaS Platforms, Internet-first Retail, Financial Services, Retail Marketplaces, On-demand Services, Travel & Ticketing Marketplaces, B2B/B2C and Direct/Indirect. This analysis helps companies build better targetting processes and lead scoring machine learning models.

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We build teams that automates anomalies search and data pre processing using efficient scripts in different languages (e.g., R/Python/C#). Data Transformation, Wrangling & Cleaning is a process of converting data into a format useful for business. It involves a range of activities including data aggregations, enrichment, conditional formatting, removing duplicates, data integration, data mapping, depending on the needs of your project. Typically our teams create scripts to automate the process and deliver cleaned data. We will host a session with our data science team to align on your infrastructure and schema before starting.

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We build dashboards in top business intelligence softwares (e.g., Looker/Tableau/PowerBI) and run basic queries in SQL. Typically, clients will create a portal access for our team, and deliver instructions on what dashboards are to be created at what cadence. We will host a session with our data science team to align on business intelligence infrastructure and schema before starting.

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We improve the search results of elasticsearch embedded in your app through elasticsearch query or using any other platform. In first phase, we optimise the elasticsearch query and try to resolve the problem of getting irrelevant results in search. The first method optimizes a few searches and we may find that we still have irrelevant results when searching a few titles. In second phase, we analyse the entire database and identify problems that exist in your database. The approach we use is that we search each title in elasticsearch using python script and try to find why it is not giving correct result.

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