Telmai is a data observability platform designed for open architecture. To learn more, Pulse 2.0 interviewed Telmai co-founder and CEO Mona Rakibe.
Mona Rakibe Background
Rakibe is an engineer turned founding product manager turned founder/CEO. Most of her career has been serving B2B enterprise needs via EMC, Oracle, BEA, and Reltio. Rakibe said:
“While at Reltio, I had a crucial role in driving the company’s product strategy and growth from its early stages to its hyper-success.”
Formation Of Telmai
How did the idea for Telmai come together? Rakibe shared:
“My co-founder, Max Lukichev, and I have a collective experience of having worked decades in the data ecosystem, and we have a deep understanding and appreciation of customer pain points. We recognized that bad data impacts all modern data initiatives, and the scale of data exacerbates the problem even further. Max is a brilliant technologist who has built distributed data systems across many startups. Through Max’s experience leading the engineering function at SignalFX (infrastructure observability), we realized the significance of using data science as a strong foundation to systematically address data reliability issues at scale. That is how the world of Observability and Data came together as “Tell me AI,” or as we call the company Telmai. Fun fact, the Sigma (Σ) in our logo refers to the mathematical foundations in our approach to solving this problem.”
Favorite Memory
What has been your favorite memory working for Telmai so far? Rakibe reflected:
“Wow, so many! Getting into Y-combinator, our first hire, first product launch, and hand-writing thank you notes to our early investors/customers. The growth we have achieved and the support we have received working in lockstep with our investment partners – .406 Ventures, Glasswing Ventures, and Zetta Ventures.”
“Like many other start-ups, I consider the tough challenges we have faced as memories of our perseverance. But my absolute favorite is – getting our first paid customer. That feeling is ecstatic!”
Challenges Faced
What are some of the challenges you have faced in building the company, and has the current macroeconomic climate affected the company? Rakibe acknowledged:
“There are quite a few, and the challenges continue to evolve as the company grows. I have embraced the mindset that start-ups are full of ambiguity and unexpected twists and turns. If I have not dealt with a new challenge for a while, we are not growing/learning and pushing ourselves hard enough.”
“As a mother of two kids, the best analogy is that it’s like having a child. No amount of books and advice can prepare you 100%. You have to go through the journey.”
“In just two years, we have experienced the SVB bank collapse, the Russia-Ukraine war impacting our team, and the effect of macroeconomics on fund-raising and pipeline velocity.”
“‘We figure things out’ is one of Telmai’s cultural pillars, which has helped train our mental model/fortitude to address these challenges head-on.”
Core Products
What are Telmai’s core products and features? Rakibe explained:
“Our primary offering is an ML-based data observability platform. The product is designed to read any data source in your heterogeneous data pipeline and extract millions of metrics (observations).”
“These observations are then used for data profiling, validation, anomaly detection, and quality monitoring across the entire data pipeline. It is improving the trust in the data fueling critical business decisions.”
“The market is rapidly moving towards advanced use cases, including Large Language Models (LLM). Today’s market tailwinds are towards extremely high-volume, high-velocity, and highly variable data. This trend reinforces the need for high-quality data at low cost. Our solution is right at the helm to address this.”
Evolution Of Telmai’s Technology
How has Telmai’s technology evolved since launching? Rakibe noted:
“The core piece of data science and architecture has remained constant, but the product has evolved to support diversity in enterprise customers’ needs, including data health KPI dashboard, more system integrations, root cause analysis features, better customizations, including bring your own (ML) model, and going from complete SaaS-only deployment to now having private cloud offerings.”
Significant Milestones
What have been some of Telmai’s most significant milestones? Rakibe cited:
— Selected to be in the Y-combinator S21 program
— We closed solid logos in 2022 before the company turned two years old.
— Closed three partnerships in Q1 2023 – Snowflake, Databricks, and Google Cloud.
— Recognized as a G2 high performer in Spring 2023 based on unanimous 5-star customer reviews.
Customer Success Stories
Upon asking Rakibe about customer success stories, she commented:
“Absolutely. One of our customers is crawling thousands of websites like Amazon.com, Walmart.com, and BestBuy.com to extract product data into a data lake for real-time analytics, such as pricing and assortment intelligence. Before Telmai, a homegrown validation service validated this web and 3rd party data against 257 data rules per source to ensure data reliability. However, with its data architecture moving from Hadoop to Snowflake, the company wanted to modernize its data quality service and ensure validations were scalable. They replaced the existing 257 data quality rules with less than 20 in Telmai and instead they are leveraging ML-based automatic validations and thresholds. This has massively improved team productivity, accelerated their time to bring better data products to the market, and significantly enhanced their top-line revenue.”
Funding
Telmai has raised $8.6 million to date, and the company’s customers are closing at a 6-figure annual recurring revenue (ARR) with multi-year contracts.
Total Addressable Market
What total addressable market (TAM) size is Telmai pursuing? Rakibe assessed:
“We have calculated the TAM for this market to be $38 billion. This calculation is based on the market opportunity within companies that have adopted cloud data infrastructures.”
Differentiation From The Competition
What differentiates Telmai from its competition? Rakibe affirmed:
Telmai has three key differentiations:
1.) Support for open architecture
Data Observability for any step/system ( data lakes, delta lakes, data warehouses, APIs, and message queues) of the data pipeline, including event streaming. With this architecture, Telmai is able to shift data quality to the left and across the pipeline.
2.) Attribute value level anomaly detection:
We analyze and observe not just metadata but also the data itself to identify drifts and outliers in the values to ensure accuracy and trust in data at scale
3.) High-performance at low-cost
Decoupled elastic architecture for petabyte-scale analysis at low TCO and predictable infrastructure cost. There is no operational overload on the observed data warehouse or other data infrastructures and no additional data validation query costs.
Future Company Goals
What are some of Telmai’s future company goals? Rakibe concluded:
“Telmai will continue to innovate in the space of data reliability via a strong foundation of data science. With our new investment and support from .406 Ventures, Glasswing Ventures, and Zetta Venture Partners, we will focus on building sales and growth functions for the company and expanding our product/engineering to address the growing market needs.”
