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How and when to use machine learning in your SaaS with CTO of $50m VC funded ML SaaS Turing.com

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Manage episode 299742054 series 2897439
Contenuto fornito da Geordie Wardman. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Geordie Wardman o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

Vijay Krishnan, CEO, and CTO of turing.com, talks about how the company developed and funded their MVP, acquired the first clients, and navigated the 0-30,000 MRR journey. Listen in.

Turing.com is a platform that pairs companies with verified global remote talent and facilitates success in the resulting collaborations. Vijay Krishnan, the CEO, is a machine learning entrepreneur and researcher. He talks to Geordie about his journey.

What You'll Learn
  • How Vijay came up with the Turing idea
  • What problem does Turing solve for their customers?
  • Remote work-based problems that Vijay and his team had to solve
  • How to make remote work effective
  • How Turing attracted its first clients
  • Why Vijay and the team decided machine learning was ideal for their platform
  • How Turing developed tests
  • Problems machine learning solves with ease
  • Tools Turing uses to operate machine learning
  • Strategies Vijay and his team are using to accelerate growth
In this Episode:

Before venturing into the machine learning world, Vijay worked in academia, industry research, and the startup sector. During that time, he gained tremendous experience dealing with a wide range of initiatives such as data science and art.

At Turing, Vijay and his team specialize in sourcing software developers from across the globe before interviewing and testing them extensively. That strategy allows Turing to develop a comprehensive profile of different developers.

According to Vijay, over 600,000 software developers from more than 10,000 cities worldwide are already registered on their platform. All of them have been pre-vetted and are ready for the job market. Vijay explains how they go about matching companies with the relevant software developer based on their needs. Listen to the podcast for the details.

Hiring the right team can be a challenging process that Vijay and his business partner faced before starting Turing. He talks about what they did to counter that challenge in this podcast. Vijay says they had sufficient experience from their previous startup when building the Turing MVP. Listen to the podcast to find out how they funded the MVP.

While working remotely is fast becoming popular, many companies are yet to embrace it. Turing's main goal was to eliminate some of the challenges hiring managers faced. Vijay sought to ensure clients enjoyed excellent quality talent, collaboration, and value. When they ventured into the market, Vijay and his team realized that they could solve a significant percentage of hiring managers' problems.

They decided to take their venture a notch higher by devising a robust global solution. Get all the details from the podcast. He also highlights various challenges in the development industry today. Vijay says they adopted all standard marketing methods like posting ads to reach potential customers.

Building an MVP and acquiring your first customer can be a prolonged process. Vijay says they first focused on building their platform, an experience that directly exposed them to pain points which they improved over time. It took them nine months before signing in their first customers. What is Turing's pricing model? Vijay says their standard model involves companies engaging with a pre-vetted software developer.

The platform, he says, allows companies to hire developers on a full-time basis after paying a fixed fee. Choosing the ideal candidate manually can be a long, frustrating process that many hiring managers are unwilling to struggle with. However, with machine learning, they have managed to ease the process. He explains why machine learning is appropriate in solving the hiring process.

With machine learning, Turing has developed an extensive profile of their software developers more robustly than what potential employers would get from a resume. While machine learning facilitates the matching process, it also assists with the test design. Vijay gives a detailed explanation of how the platform works. You cannot afford to miss this part of the podcast.

The prevailing pandemic has affected nearly all businesses across the world in various ways. Vijay says the market experienced shock with people not knowing what was happening at the beginning of the pandemic. A few months in and Turing started experiencing massive growth. He mentions that some of the people who had resented remote work previously started embracing it. Developers do not pay to join the Turing platform.

Resources

Vijay Krishnan LinkedIn

Vijay Krishnan Twitter

Turing.com

  continue reading

100 episodi

Artwork
iconCondividi
 
Manage episode 299742054 series 2897439
Contenuto fornito da Geordie Wardman. Tutti i contenuti dei podcast, inclusi episodi, grafica e descrizioni dei podcast, vengono caricati e forniti direttamente da Geordie Wardman o dal partner della piattaforma podcast. Se ritieni che qualcuno stia utilizzando la tua opera protetta da copyright senza la tua autorizzazione, puoi seguire la procedura descritta qui https://it.player.fm/legal.

Vijay Krishnan, CEO, and CTO of turing.com, talks about how the company developed and funded their MVP, acquired the first clients, and navigated the 0-30,000 MRR journey. Listen in.

Turing.com is a platform that pairs companies with verified global remote talent and facilitates success in the resulting collaborations. Vijay Krishnan, the CEO, is a machine learning entrepreneur and researcher. He talks to Geordie about his journey.

What You'll Learn
  • How Vijay came up with the Turing idea
  • What problem does Turing solve for their customers?
  • Remote work-based problems that Vijay and his team had to solve
  • How to make remote work effective
  • How Turing attracted its first clients
  • Why Vijay and the team decided machine learning was ideal for their platform
  • How Turing developed tests
  • Problems machine learning solves with ease
  • Tools Turing uses to operate machine learning
  • Strategies Vijay and his team are using to accelerate growth
In this Episode:

Before venturing into the machine learning world, Vijay worked in academia, industry research, and the startup sector. During that time, he gained tremendous experience dealing with a wide range of initiatives such as data science and art.

At Turing, Vijay and his team specialize in sourcing software developers from across the globe before interviewing and testing them extensively. That strategy allows Turing to develop a comprehensive profile of different developers.

According to Vijay, over 600,000 software developers from more than 10,000 cities worldwide are already registered on their platform. All of them have been pre-vetted and are ready for the job market. Vijay explains how they go about matching companies with the relevant software developer based on their needs. Listen to the podcast for the details.

Hiring the right team can be a challenging process that Vijay and his business partner faced before starting Turing. He talks about what they did to counter that challenge in this podcast. Vijay says they had sufficient experience from their previous startup when building the Turing MVP. Listen to the podcast to find out how they funded the MVP.

While working remotely is fast becoming popular, many companies are yet to embrace it. Turing's main goal was to eliminate some of the challenges hiring managers faced. Vijay sought to ensure clients enjoyed excellent quality talent, collaboration, and value. When they ventured into the market, Vijay and his team realized that they could solve a significant percentage of hiring managers' problems.

They decided to take their venture a notch higher by devising a robust global solution. Get all the details from the podcast. He also highlights various challenges in the development industry today. Vijay says they adopted all standard marketing methods like posting ads to reach potential customers.

Building an MVP and acquiring your first customer can be a prolonged process. Vijay says they first focused on building their platform, an experience that directly exposed them to pain points which they improved over time. It took them nine months before signing in their first customers. What is Turing's pricing model? Vijay says their standard model involves companies engaging with a pre-vetted software developer.

The platform, he says, allows companies to hire developers on a full-time basis after paying a fixed fee. Choosing the ideal candidate manually can be a long, frustrating process that many hiring managers are unwilling to struggle with. However, with machine learning, they have managed to ease the process. He explains why machine learning is appropriate in solving the hiring process.

With machine learning, Turing has developed an extensive profile of their software developers more robustly than what potential employers would get from a resume. While machine learning facilitates the matching process, it also assists with the test design. Vijay gives a detailed explanation of how the platform works. You cannot afford to miss this part of the podcast.

The prevailing pandemic has affected nearly all businesses across the world in various ways. Vijay says the market experienced shock with people not knowing what was happening at the beginning of the pandemic. A few months in and Turing started experiencing massive growth. He mentions that some of the people who had resented remote work previously started embracing it. Developers do not pay to join the Turing platform.

Resources

Vijay Krishnan LinkedIn

Vijay Krishnan Twitter

Turing.com

  continue reading

100 episodi

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