Who We Are

Leastsquare Inc. is a privately held financial, software, and data company founded in 2023 and headquartered in New York.

We are an early-stage company and are currently growing the founding team. If you feel passionate about our mission and want to join or support us, please reach out at

Our Mission

Our mission is to provide the technology, facts, and insights that advance financial and investment decision-making.

Our Story

Why Our Mission Is Critical

Financial stability and inclusion improve lives. In contrast, uncertainty about the future takes away from enjoying and focusing on the present. That is not just true for individuals but also for organizations. In fact, predictability does not just feel good; it is core to economic value creation. Effective resource allocation hinges on accurate financial forecasting. At Leastsquare Inc., we aim to provide the accuracy in financial data and projections that transforms organizations' operations. With a clear forecast, you can allocate resources wisely, align people around a clear vision, plan confidently, and dedicate your full attention to executing your business strategy.

“Financial stability and inclusion improve lives.”

Sharif Ismail,
Founder of Leastsquare Inc.

This clarity impacts every level of an organization. It means marketing teams can budget campaigns that resonate with their audience. It allows HR departments to hire with foresight and product development teams to innovate with the assurance that their projects are backed by solid financial planning. It's about giving companies the power to exceed customer expectations, enrich their communities, support their suppliers, and deliver value to shareholders and employees.

Our Plan

We tackle the problem head-on. The root of uncertainty is not knowing what will happen. In other words, lack of knowledge and information is a core problem. Accordingly, the road to stability is paved through accurate information about the present and future that is aligned with and accessible to everyone involved.

Our plan is to make access to advanced financial analyses simple. Today, business planning, forecasting, and analyses are notoriously complex. It is hard to get relevant data, connect the bits and pieces that matter to you, and analyze it in a way that creates genuine confidence among stakeholders.

We want to change that, and we believe with recent advances in machine learning, we will be able to push the boundaries and provide an easy-to-use interactive chat interface that is powered by sophisticated financial models with access to real-time public financial data so that you can ask, tell, copy, and paste your way to what you need and should know.

How It Will Work

Forecasting and financial analyses are not just tricky for humans; they are also challenging for machines, with various open challenges.

Hence, we will break up our journey in multiple steps.

At first, we will provide embeddings for economic entities, meaning individual companies, governments, or other organizations that operate in the economy. Those embeddings compress high-quality public information about an economic entity into one single vector. Thus, they work similarly to sentence embeddings from large language models. We call them Contextual Entity Embeddings (CEEs), and they can be used in various machine learning tasks, such as forecasting, classification, anomaly detection, and predictions. Our embeddings are unique in that they capture contextual information from the environment in which organizations operate, again using high-quality public information. After all, the future of a business is only partially determined by itself. A lot of information lies in an organization's customers, competitors, suppliers, and markets. Infusing contextual knowledge significantly increases the accuracy of the predictions while maintaining the simplicity of having one single vector of data to work with.

Building upon our Contextual Entity Embeddings (CEEs), our second step is to provide comprehensive API access to our full pre-trained financial model. This expansion allows easier access to relevant information without additional processing or modeling on the user side. The Model API enables developers to tap into a wellspring of financial foresight, using our model’s extensive analytical prowess using only Natural Language and to integrate their own datasets without the need to build a custom model.

Finally, after we have pre-trained our model, we will provide an interactive chat interface to enable not just developers to tap into the insights of our model but every individual and organization to benefit and perform sophisticated financial analyses using only natural language with the convenience of having historical and actual public data built-in.

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