Pantomath is a data pipeline observability and traceability platform for automating data operations. Pulse 2.0 interviewed Pantomath CEO and founder Somesh Saxena to learn more about the company.
Somesh Saxena’s Background
Could you tell me more about your background? Saxena said:
“I’ve spent much of my career working in data and analytics. Before founding Pantomath, I led data and analytics efforts at General Electric Aerospace, where I supported 18,000 data consumers through a 100-person team. My responsibilities spanned enterprise data and analytics, self-service data, big data, data governance, and robotic process automation, giving me a deep understanding of the challenges data teams face.”
Formation Of The Company
How did the idea for the company come together? Saxena shared:
“From my own experience and conversations with industry peers, I’ve seen how companies aim to be data-driven—building dashboards, analytics, and data pipelines within the modern data stack—yet still grapple with data reliability problems. These issues often lead to poor decision-making and erode trust in the data, ultimately affecting business performance. Fixing these problems is usually a slow, manual process involving multiple teams and requiring extensive knowledge to trace the root cause across complex data pipelines, resulting in lost productivity and data downtime. The idea of Pantomath was born out of this major pain point experienced by both data teams and data consumers. The vision was to build a product that provides end-to-end observability and traceability across the data stack allowing teams to detect issues in real time, simplify troubleshooting, and resolve incidents instantly.”
Favorite Memory
What has been your favorite memory working for the company so far? Saxena reflected:
“One of the most amazing moments I’ve had in the company is the day we launched our first customer. Our software solution automatically drew out every single complex data pipeline across their entire data ecosystem. This technology that auto-discovers inter-system data pipelines did not exist before this. Our team worked tirelessly to build this innovative product and seeing it come to life is a memory I’ll always cherish.”
Core Products
What are the company’s core products and features? Saxena explained:
“Core Products
— Data Observability Platform: Provides end-to-end visibility into data pipelines, helping teams monitor, troubleshoot, and maintain their data systems’ reliability.
— Pipeline Traceability: Helps users track the flow of data across various systems, ensuring they can identify, trace, and resolve any issues in data pipelines.
— Data Reliability: Ensures data is accurate, complete, and reliable, supporting key decision-making processes.
— Data Quality Monitoring: Automated monitoring of data quality with alerts on potential anomalies or issues, ensuring data meets defined standards.
Key Features:
— True End-to-End Monitoring: Provides real-time insights and continuous monitoring across the entire data stack, from ingestion to transformation to consumption.
— Anomaly Detection: Uses machine learning algorithms to detect unexpected changes or anomalies in data patterns, which helps prevent bad data from impacting business operations for both data at rest and data in motion.
— Root Cause Analysis: Quickly identifies the root causes of data issues by offering detailed insights into the data pipeline’s performance and health.
— Impact Analysis: Understand downstream impact of data issues and a guided path to resolution through end-to-end traceability significantly decreasing the time from error to resolution.
— Customizable Dashboards: Tailored dashboards that allow teams to visualize data performance metrics and track relevant KPIs.
— Actionable Alerts and Notifications: Sends out notifications to the right data engineers and stakeholders when issues are detected in the pipeline or data quality degrades, helping teams respond quickly to problems. You are able to designate different teams to the parts of the pipeline that they are responsible for or the type of issue that is occurring, leading to reduction in alerting noise.
— Compliance and Governance Support: Ensures data governance policies are adhered to, including audit trails, access controls, and compliance reporting.
Evolution Of The Company’s Technology
How has the company’s technology evolved since launching? Saxena noted:
“Like any software company, our technology has gone through a natural maturity curve. We initially built it for speed, not scale. We wanted to stay lean to go fast and prove to ourselves that we could build the innovative functionality we set out to create. And then started scaling it up incrementally from there for our customers. And as both the size of our customer environments and customer base grew, we had to continue scaling up and mature our technology to meet the higher volume and complexity demands. Since the majority of our customers are large enterprises, we’ve had to go through this maturity curve relatively quickly.”
Significant Milestones
What have been some of the company’s most significant milestones? Saxena cited:
“A few of the most significant milestones include raising our first round of venture capital, bringing the initial team together in our office on the first day, the day we first launched our product with customer #1 and hearing from all our happy customers about the value Pantomath is adding and how they start and end their day with our product.”
Customer Success Stories
When asking Saxena about customer success stories, he highlighted:
Paycor: Pantomath helped Paycor significantly improve billing predictability and reliability by providing end-to-end data observability. This allowed Paycor to identify and fix data issues weeks before they could impact invoices, cutting down remediation time from days to hours.
TQL: Pantomath has given TQL’s data team more insight into their data and its dependencies while also helping understand the usage and accuracy of reports for migration from on prem to the cloud. They can now understand exactly what data is being used – and the team has been able to reduce the number of BI reports from more than 3,000 to under 500.
Lendly: Pantomath enabled Lendly to monitor their data pipelines proactively, reducing time spent troubleshooting and improving the reliability of their critical customer-facing processes.
Coterie: Pantomath’s data observability allowed Coterie to detect data quality issues in real-time, ensuring smooth operations and faster issue resolution.
Funding
When asking Saxena about the company’s funding details, he revealed:
“Pantomath raised $14 Million in Series A led by Sierra Ventures on October 16th, 2023 and anticipating a Series B raise in the very near future. Based on revenue and other metrics, Pantomath is one of the fastest growing startups in the country and we’re just getting started.”
Total Addressable Market
What total addressable market (TAM) size is the company pursuing? Saxena assessed:
“The problem of data reliability and data quality issues is rampant across most organizations, especially large enterprises that are striving to be data-driven. We see a future where Pantomath enables thousands of enterprises across the world with healthy and reliable data.”
Differentiation From The Competition
What differentiates the company from its competition? Saxena affirmed:
“What sets Pantomath apart is that its competitors primarily focus on data quality, monitoring data-at-rest which is only a piece of the puzzle. Pantomath on the other hand continuously monitors both data at rest and job-related operational data in motion issues in real-time that make up a data pipeline across different data platforms, all with the context of the data pipeline(s) those jobs and datasets are a part of, so users know exactly what is broken, where it’s broken, and why it’s broken. It enables observability and traceability across the entire data pipeline to ensure real-time resolution of both data quality incidents and job-related operational incidents. Unlike other data observability solutions that are simply a “check engine light” for their users, Pantomath acts as a problem-solving diagnostics tool that gives car mechanics the instant root cause of the issue and enables faster time to resolution.”
Future Company Goals
What are some of the company’s future company goals? Saxena concluded:
“We’re developing innovative GenAI features designed to automate root-cause analysis for data reliability and quality issues, as well as enable fully automated self-healing for data pipelines. This will transform how organizations manage and maintain their data pipelines, significantly improving productivity, reducing resolution times, and fostering greater trust in data to support a truly data-driven culture.”
