Top MLOps Startups in India :
Machine learning (ML) has been a buzzword going around the tech industry for quite some time. With technological advancements, AI applications have grown rapidly due to a high demand for infrastructure and software that supports AI applications. Many start-ups have been joining this field of MLops.
What is MLOps ?
Why MLOps is Important ?
Now a days almost every other organisation is trying to incorporate AI/ML into their product. This new requirement of building ML systems adds/reforms some principles of the SDLC to give rise to a new engineering discipline called MLOps.
Here are top emerging MLOps Startups in India you should check out-
1. OpsLyft
| Startup Name | OpsLyft |
| Legal Name | OpsLyft Inc. |
| Founders | Aayush Kumar |
| Start Year | 2020 |
| Funding | $ 700K , SEED |
| Investors | Anand Chandrasekaran, Rajesh Yabaji, Abhinav Shashank, Sandeep Gupta, Kanav Hasija |
| No. Of Employees | 21 to 40 |
| Contacts | contact@opslyft.com |
| Head Office | San Francisco, California, United States |
| Official Website | https://opslyft.com/ |
OpsLyft Inc. is a San-Francisco & Noida-based technology company working towards building the future of cloud infrastructure management for internet companies across the World. OpsLyft, founded by Aayush Kumar, is developing a full-stack DevOps observability and automation platform to help engineering managers, executives, and DevOps teams save time, effort, and money on cloud infrastructure management.
OpsLyft is presently working with some of India’s most successful high-growth startups, such as Inshorts, Innovaccer, Zenoti, Purplle and others.
Its Platform Overview :-
Cost 360 :
Cost360 is a cloud spend management platform that analyzes the cloud resources in real-time to give software developers insights and suggestive actions for making cost-friendly infrastructure changes.
- Cloud Cost Budgeting & Predictability.
- Map Cloud Costs to Business Metrics.
- Infrastructure Cost & Usage Visibility.
- Infrastructure Management.
Funding :
It has received $500k in seed funding from Anand Chandrasekaran, the founder of a unicorn company, as well as well-known angel investors from Freshworks, Oyo, and Innovaccer in India and the US.
These funds will be used by OpsLyft to accelerate product development, strengthen the team, and expand go-to-market functions in the US.
2. AIVIDTechVision
| Startup Name | AIVID TechVision |
| Legal Name | AIVID TechVision Pvt Ltd |
| Founders | Nikhil Jain, Dhaval Vora |
| Start Year | 2020 |
| No. Of Employees | 21 to 40 |
| Contacts | info@aividtechvision.com, +91 7948993215 |
| Head Office | Ahmedabad, Gujarat 380054 |
| Official Website | https://www.aividtechvision.com/ |
3. DataOrc
| Startup Name | Dataorc |
| Legal Name | Dataorc LLP. |
| Founders | Mayur Jadhav, Navdeep Agarwal |
| Start Year | 2018 |
| No. Of Employees | 1 to 10 |
| Contacts | contactus@dataorc.in, |
| Head Office | Pune, Maharashtra, India |
| Official Website | https://www.dataorc.in/ |
DataOrc was founded by Mayur Jadhav and Navdeep Agarwal in 2018. The company enables businesses to make data-driven decisions. DataOrcs builds practical machine learning solutions with data, right from POCs to deploying machine learning models.
What They Do ?
- Data Engineering : Building robust, scalable, fault tolerant and cost effective Data platforms which enables organizations to draw insights from data fast and easy.
- Product Engineering: Product engineering at scale with primary focus on performance, scalability, least time-to-market.
- Machine Learning : Building practical machine learning solutions with the precious data. Right from POCs to scalable deployment of models.
Product :
- Data Syncer(Beta) :It helps in building insightful data streams from existing application stores without having you write a line of code.
4. Tredence
| Startup Name | Tredence |
| Legal Name | Tredence Inc |
| Founders | Shub Bhowmick, Shashank Dubey, Sumit Mehra |
| Start Year | 2018 |
| Funding | $ 30 M |
| Investors | Chicago Pacific Founders |
| No. Of Employees | 501 to 1000 |
| Contacts | info@tredence.com |
| Head Office | Gurgaon, Haryana India; San Jose, California, US |
| Official Website | https://www.tredence.com/ |
Tredence is an AI engineering and analytics company that uses its ML works platform to industrialise and accelerate MLOps.
Its industrialised machine learning operations platform ‘ML Works’ helps enterprises manage several AI customer engagements. It allows them to scale machine learning models, reduce outages in the machine learning pipeline, and simplify model monitoring.
The world’s largest corporations are collaborating with Tredence and deploying its prediction and optimization solutions at scale, empowering end-users to make better decisions. Tredence also has a track record of delivering business impact to Fortune 500 customers.
Funding
Tredence has received a nearly $30 million investment from Chicago Pacific Founders, a strategic healthcare investment fund.
5. Scribble Data
| Startup Name | Scribble Data |
| Legal Name | Scribble Data Inc |
| Founders | Venkata Pingali, Indrayudh Ghoshal |
| Start Year | 2017 |
| Funding | $ 2.2 M |
| Investors | LogX Ventures, Blume Ventures, Sprout Venture Partners |
| No. Of Employees | 501 to 1000 |
| Contacts | hello@scribbledata.io |
| Head Office | Indiranagar, Bangalore, India ; Toronto, Ontario, Canada |
| Official Website | https://www.scribbledata.io/ |
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Scribble Data is an MLOps product company that provides the building blocks for enterprises to build their ML models and analysis. It offers a machine learning feature store for data teams of mid-market enterprises.
Scribble Data also assists businesses in developing and managing production-ready datasets needed to scale machine learning and analytical use cases and applications.
Product :
Enrich : Enrich handles the complexity of computation and data semantics by providing a python SDK to develop, document and test the feature engineering modules (transforms, pipelines, scheduling, etc) and controlled execution on the server-side.
So for Data Scientists, the Enrich feature store experience simplifies, standardizes, and speeds up the machine learning model deployment pipeline, with confidence in their performance.
Funding :
Scribble Data raises $2.2 million in seed funding led by Blume Ventures. The round also saw participation from Log X Ventures and Sprout Venture Partners.
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