- Sector
- Software and data methods for formulation research
- Ownership
- Founders 55%, employee trust 25%, private family investment vehicle 20%; trust beneficiary without direct shares
- Company scale
- ₹83 crore revenue and ₹9.8 crore operating profit, FY ending March 2026
- Employees
- 215 company employees
- Geography
- Puducherry headquarters; 48 client organisations
- Reporting to
- CEO Anita Qevrasi
- Team
- 42 data colleagues through four heads
- Financial scope
- ₹12.4 crore FY 2026–27 operating expense; separate ₹3.1 crore data-quality capital programme
Mandate
Connect experimental context, software interpretation and the scope of research-product promises
Outcomes
- Funded a revised sensory-study schedule instead of releasing a position-confounded ranking
- Restored qualified laboratory results and their reporting limits in the import workflow
- Narrowed a proposed shelf-life feature and retained the smaller forecast and unfinished redesign
Decisions in context
I became CDO in March 2022 and report to CEO Anita Qevrasi. I lead 42 colleagues through four heads, with ₹12.4 crore FY 2026–27 operating expense and a separate ₹3.1 crore capital programme for data quality. The company serves 48 organisations through 215 employees and recorded ₹83 crore revenue with ₹9.8 crore operating profit in FY 2026. My decisions connect the experimental meaning of data with product scope and resource commitments. They include a delayed panel comparison, restored laboratory qualifiers and a narrower trend-view proposition. Scientific methods lead Peter Qezvomi and client professionals retain their expertise and responsibilities; the data role does not certify a formulation. I want the investment account to retain added costs, deferred programmes and forecast reductions as well as completed improvements. I have no statutory directorship alongside this executive appointment, and any outside contribution would require a separate assessment of fit and capacity.
Reason for the move
Continuing the CDO remit while assessing a first outside board contribution
- Sector
- Data methods for experimental formulation software
- Ownership
- Privately held founder-led company
- Company scale
- ₹57 crore company revenue in FY ending March 2018
- Employees
- 160 company employees
- Geography
- Puducherry product and data-methods organisation
- Reporting to
- Chief Executive Officer
- Team
- 27 colleagues through three heads
- Financial scope
- ₹6.7 crore annual data-methods expense
Mandate
Make research assumptions visible in product interpretation and demonstration decisions
Outcomes
- Took enterprise responsibility for the data-methods programme
- Withdrew my own standalone ingredient-effect interpretation after reviewing the full blend movement
- Supported funded experimental review and revised composition displays
Decisions in context
The June 2017 appointment expanded my responsibility from data modelling into the methods our product used to explain research. I managed 27 colleagues through three heads and ₹6.7 crore annual expense, reporting to the CEO. Vemqari had 160 employees and ₹57 crore FY 2018 revenue. The most consequential judgement in this period was a 2019 interpretation I approved. Four blends increased one component while decreasing another within a fixed total. I allowed the explanation to attribute the response to the first component alone. After Peter Qezvomi challenged the comparison, I withdrew that claim and supported ₹32 lakh for review and a revised study design. The observations remained records of the blends actually tested. I learnt to connect an explanatory weakness with product requirements and funded work, rather than relying on a qualification added after the main story had been chosen. That responsibility led into the wider CDO appointment.
Reason for the move
Appointed CDO in March 2022
- Sector
- Formulation-research data modelling and software
- Ownership
- Privately owned research-software enterprise
- Company scale
- FY 2012 revenue of ₹22 crore
- Employees
- 85 company employees
- Geography
- Puducherry software product team
- Reporting to
- Product Director
- Team
- 14 colleagues through two leads
- Financial scope
- ₹2.8 crore annual data-modelling expense
Mandate
Represent research observations and their conditions in a reusable software product
Outcomes
- Moved from study-service delivery into product data modelling
- Brought experimental arrangements into discussions of fields, imports and outputs
- Built working relationships between scientific, product and engineering colleagues
Decisions in context
I joined Vemqari in September 2011 and moved to Puducherry. The company employed 85 people and recorded ₹22 crore revenue in FY 2012. I led 14 colleagues through two leads with ₹2.8 crore annual expense, reporting to the product director. Moving from research services into software changed the scale of a data decision. A representation chosen for a product could be repeated across many customer studies, including contexts its designer had not imagined. I worked with scientific and engineering colleagues to preserve the conditions that made an observation intelligible. The work also required practical choices about what the interface could ask a researcher to supply and explain. I did not own each customer's experimental programme. I owned a team whose modelling choices could either help that customer inspect the programme or make important distinctions harder to see. This period established the product perspective behind my subsequent methods leadership.
Reason for the move
Promoted to director of data methods in June 2017
4Feb 2005 — Aug 2011
Research Data Lead
Qevmari Sensory Research
- Sector
- Sensory-study research and data services
- Ownership
- Privately held regional research enterprise
- Company scale
- ₹26 crore revenue for FY ending March 2006
- Employees
- 135 company employees
- Geography
- Patiala-based study and research-data teams
- Reporting to
- Research Director
- Team
- 11 colleagues through two leads
- Financial scope
- ₹1.6 crore annual research-data expense
Mandate
Organise study-data work without erasing differences in the experimental arrangements
Outcomes
- Took formal people and expense responsibility
- Built review time into the handling of ambiguous observations
- Connected consistent data formats with the limits of comparison between studies
Decisions in context
I became research data lead in February 2005, supervising 11 colleagues through two leads and ₹1.6 crore annual expense under the research director. Qevmari had 135 employees and ₹26 crore FY 2006 revenue. I had to make the team's work consistent while recognising that studies could differ in ways a shared table did not reveal. A presentation sequence or a reporting qualification was part of the research account, not an inconvenience to remove in the name of uniformity. Managing the function made me responsible for the time spent resolving those questions. I learnt to explain why a complete collection of rows might still need review before analysis. The role did not make me the scientific authority for every study; it taught me to organise collaboration with the people who held that responsibility. I left in August 2011 to apply that experience within a software product.
Reason for the move
Joined Vemqari in September 2011 to work on formulation software
5Jul 1998 — Jan 2005
Study-data Analyst
Qevmari Sensory Research
- Sector
- Sensory research and study-data preparation
- Ownership
- Privately owned regional business
- Company scale
- Company revenue of ₹7.9 crore in FY 1999
- Employees
- 52 company employees
- Geography
- Patiala research office
- Reporting to
- Research Manager
- Team
- Member of a six-person study group; no direct reports
- Financial scope
- No delegated spending authority
Mandate
Prepare observations while retaining the conditions needed to understand them
Outcomes
- Learnt to distinguish an observed score from an interpretation of the study
- Asked about sequence and missing observations before finalising data records
- Developed the statistical and collaborative foundation for research-data leadership
Decisions in context
My first appointment began in July 1998 after completing the applied-statistics master's degree the previous month. I worked in a six-person study group under a research manager, without staff or budget authority. Qevmari employed 52 people and recorded ₹7.9 crore revenue for FY ending March 1999. The work involved making study observations usable for colleagues who would analyse them. I learnt that the same-looking score could carry different context depending on when and how it had been obtained. Asking about that context was part of careful preparation, even when it interrupted an apparently straightforward table. I was not directing the research or deciding the business proposition. I was learning how to preserve the distinction between a record and a conclusion. The experience developed my interest in data representation and gave me a practical basis for taking responsibility for a team in 2005.
Reason for the move
Promoted to research data lead in February 2005
What I am looking for next
I am considering a first outside contribution where a board needs to understand the evidence behind a research-dependent product or investment. I would bring experience of experimental assumptions, software interpretation and the commercial consequences of narrowing a promise. The receiving enterprise would also need financial, sector and governance expertise beyond my specialism. I have no statutory board seat. This fictional record includes April 2026 IICA registration and an August proficiency-assessment pass without an exemption; those preparation steps do not settle eligibility or independence for a particular appointment. Twenty-four provisional days must cover induction, reading, travel, meetings and exceptional work alongside the CDO remit. Employer consent and a review of trust interests, clients and other relationships would precede any commitment. I would seek a chair who can help me learn the whole enterprise and colleagues willing to challenge my own interpretation. The next chapter should make collective judgement more effective, while leaving scientific and operating decisions with the people responsible for them.