Gunbir Sethi Gauba and the value of a better question

A spreadsheet is an oddly persuasive object. Put enough numbers in straight lines and even a fragile assumption can acquire the manners of a fact. Gunbir Sethi Gauba’s working life has taken her through the institutions where those assumptions are raised, examined and put to use: investment banks, an equity research team and, eventually, a company of her own.

She is the co-founder and co-CEO of InSync Analytics, which she built with Pinkey Jain. Founded in 2006, the business now sits inside the argument over what artificial intelligence should do for investment research. Its September 2026 A(I)mplified Analyst offering pairs a dedicated researcher with financial data and AI tools. The person remains part of the proposition.

That choice gives Gauba’s career its present tension. Having worked as an analyst, she is helping build technology that changes the analyst’s day. The question is how much of that day can be returned to thinking. Finance has never suffered from a shortage of spreadsheets. Finding enough time to interrogate them is another matter.

A career spent inside the numbers

Before business school, Gauba worked in investment banking at Merrill Lynch / Smith New Court Securities. Her work included more than $5 billion in capital raising transactions. She earned an MBA at New York University’s Stern School of Business and holds a Diploma in Financial Management from Maastricht School of Management in the Netherlands.

At JP Morgan, she worked in the Global Industrials group in New York, executing more than $10 billion in advisory transactions. She subsequently worked as an equity analyst in the Global Media team at Banc of America Securities, including its Institutional Investor-ranked broadcasting team. The progression moved her from transactions into the continuing scrutiny of public companies.

These are distinct vantage points on the same enterprise. A banker helps a company raise money or navigate a transaction. An equity researcher examines the business as an investment. Revenue, margins and expectations appear in both settings, although the question being asked changes. Gauba’s professional background spans both kinds of work.

Her co-founder brought a related background. Jain had worked in investment banking at JP Morgan and Harris Nesbitt in New York, covering telecommunications, media and technology. Together they established a women-owned company serving investment professionals. The partnership placed banking and research experience close to the practical business of preparing financial models.

The business also makes training part of its operating method. Its staff includes people from banking, research and corporate backgrounds, with business and engineering qualifications as well as CFA and MBA credentials. In-house training covers company research, financial modeling, accounting treatments, valuation and compliance. Those subjects help explain why the human part of the business persists as the technology changes. A tool can retrieve a number; the work still requires people who understand what the number represents and how it should be used.

Four words, one working problem

InSync’s shorthand for its current business is GAME: guidance, actuals, models and estimates. Gauba uses the acronym in her public posts. It is a tidy name for information that can become untidy remarkably quickly. A company says what it expects, reports what happened, and leaves analysts to decide what comes next.

The distinction between those categories matters. Guidance comes from management. Actuals describe reported performance. Estimates express forecasts, including those made by sell-side analysts. Models connect assumptions to financial outcomes. Put them next to one another and a researcher can ask where expectations changed, which operating measure explains the movement and what the change does to a valuation.

InSync’s consensus business draws on working sell-side models, with access governed by research entitlements. Its approach links reported metrics with their corresponding estimates. That connection is useful because a row label alone cannot do all the interpretive work. A forecast needs a definition, a period and a relationship to the figure against which it will eventually be judged.

The historical-data business supplies another part of the picture: company filings, supplemental materials, investor presentations and earnings transcripts. Its coverage includes reported financials, operating measures, management guidance and accounting adjustments. A longer record lets an analyst examine how a business has changed before making an argument about where it might go.

The company also offers pre-built models that users can customize in Excel. These include segment information and operating measures such as volumes, selling prices, customer growth and churn. Such details bring a model closer to the actual mechanics of a business. A total at the bottom of a statement is more useful when the analyst can examine the moving parts above it.

A new job description for the analyst

On September 17, 2026, InSync announced A(I)mplified Analyst. The offering combines a dedicated, buy-side-trained researcher with the company’s data and AI tools. InSync said its existing embedded-analyst service was already used by more than 100 hedge funds and asset managers across the United States and EMEA. The launch added a more integrated technology proposition to that service.

“The analyst role isn't going away; it's being elevated.”

Gunbir Sethi Gauba · September 2026

The job remains recognizably research. Tasks include reconciling earnings against guidance and consensus, following broker revisions, assembling comparable-company analysis and building models. The change lies in how the ingredients reach the researcher and how much of the preparation can be repeated through a defined workflow. Gauba’s stated ambition gives human judgment a continuing place in that arrangement.

InSync’s MCP connection allows AI applications to query its structured financial dataset. MCP, short for Model Context Protocol, is the connection between an AI tool and outside information or tools. Here the practical purpose is access: a researcher can bring the data into a supported AI environment rather than repeatedly assembling it by hand.

WEAVE takes the work into Excel. InSync describes it as an AI modeling assistant, available to current clients through early beta access. Its functions include questions about a model’s structure, live data retrieval, scenario analysis and annotations. These are proposed aids to the same activity Gauba once practiced professionally: examining how the numbers fit together.

There is a useful modesty in the underlying question, even when the technology vocabulary becomes elaborate. Which assumption changed? Where does it flow through the statements? What happens if it is wrong? A model can make those questions easier to explore. The investment professional still has to decide which answer carries weight.

The delivery choices acknowledge where that work already happens. InSync offers a web platform called ISTARI, an Excel add-in, APIs and datafeeds alongside the MCP connection. A fund can use a prepared model, adapt it to its own view or bring data into its internal systems. For Gauba’s company, the product reaches into an existing research routine. The familiar spreadsheet remains on the desk, even as new ways of questioning it arrive.

The questions coming from the classroom

Gauba has also taken the discussion outside the investment office. She spoke at Columbia University’s pre-college Entrepreneurship & Innovation program on AI and the future of business. In her public account, she acknowledged mixed feelings about young people entering a workforce undergoing substantial change, while expressing confidence in their ability to innovate.

Michael Esposito, who welcomed her to the program, described a conversation shaped by students’ questions about entrepreneurship, innovation, leadership and the realities of building a business. The exchange offers a different view of a founder whose company usually speaks to professional investors. Here the audience was still approaching the beginning of working life.

Her reaction was encouraging, but it made room for uncertainty. That combination is appropriate to the subject. A founder can build tools for the next version of a job while recognizing that the people entering it face difficult questions. Her public response to the students was confidence in their capacity to make something of the change.

The other work on her desk

There is another organization in Gauba’s life, with an acronym that needs less explanation in a classroom. She is founder and president of HEAL Foundation: Humanity, Empathy, Animal Love. The nonprofit’s mission includes reducing canine homelessness and supporting animal-welfare organizations. Humane education for young people is part of its work as well.

HEAL’s education mission encourages empathy, compassion and respect for people, animals and the environment. Its animal-welfare work includes support for organizations helping dogs that can be harder to place, including older dogs and bonded pairs. That gives the foundation a practical focus within the broad language of compassion.

InSync connects the charitable work to the business through a stated commitment to donate ten percent of profits to HEAL and other charities. Its community activity in India has also included beach cleaning, tree planting and support for Habitat for Humanity’s water-wheel distribution project in Karjat, Maharashtra. The company describes about 200 water wheels reaching families.

Those activities belong alongside the banking appointments and product launches in an account of Gauba’s working life. The company she co-founded builds systems for examining financial information. The foundation she founded directs attention toward animals and humane education. Each has a defined job to do, with people responsible for carrying it out.

Back at the analyst’s desk, the next chapter is still being worked through. Gauba’s company is changing the machinery around research while keeping the researcher inside the process. Her own path gives that decision context: she has raised capital, worked on advisory transactions and examined companies as an analyst. Now she helps build the tools. The better question still needs someone to ask it.