How Space Startup Pixxel Uses AI To Monitor Earth

Early last year, the Indian Government decided to open up the space sector to private players. “The Department of Space will promote sector space activities to enable it to provide end to end space services, including building and launching of rockets and satellites as well as providing space-based services on a commercial basis,” ISRO chief K Sivan had said.

Read more: https://analyticsindiamag.com/how-space-startup-pixxel-uses-ai-to-monitor-earth/

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How This Startup Is Using AI For Talent Acquisition

Talent acquisition is one of the significant challenges that companies across all the major domains face. Even if the right candidate is hired, retaining them is another challenge that companies have to deal with. Companies are now exploring new-age technologies such as AI to deal with this crisis. And, to facilitate these intelligent solutions are startups such as Eightfold, which claims to be the industry’s first talent intelligence platform built for enterprises to address talent acquisition and management holistically.

Founded by Ashutosh Garg and Varun Kacholia who have extensive experience in building AI programs in large technology companies, wanted to apply the experiences learnt in AI into talent acquisition. That’s how Eightfold AI was born to use AI to provide the best career to everyone. The team currently has 200 employees with a strong tech team.

Analytics India Magazine got in touch with Vinodh Kumar Ravindranath, Head of Artificial Intelligence at Eightfold.ai to understand more about their AI game for talent acquisition and how they stand different from other players.

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“It is the first talent intelligence platform that large companies have for the whole employee lifecycle starting from screening to layoff avoidance,” he said.

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#startups #eightfold ai #eightfold ai startup #ai

Making Sales More Efficient: Lead Qualification Using AI

If you were to ask any organization today, you would learn that they are all becoming reliant on Artificial Intelligence Solutions and using AI to digitally transform in order to bring their organizations into the new age. AI is no longer a new concept, instead, with the technological advancements that are being made in the realm of AI, it has become a much-needed business facet.

AI has become easier to use and implement than ever before, and every business is applying AI solutions to their processes. Organizations have begun to base their digital transformation strategies around AI and the way in which they conduct their business. One of these business processes that AI has helped transform is lead qualifications.

#ai-solutions-development #artificial-intelligence #future-of-artificial-intellige #ai #ai-applications #ai-trends #future-of-ai #ai-revolution

How This Cybersecurity Startup Is Using Machine Learning

The COVID pandemic has massively escalated the surge of cyberattacks and data breaches despite having robust security controls, software, and solutions abundantly available in the market. A lot of this could be attributed to the vulnerability businesses offer the cybercriminals to take advantage of the situation quickly. While the conventional cybersecurity approach has benefited many, having cybersecurity without cyber-intelligence and necessary awareness can put the security professionals off-guarded to more complicated and novel threats.

Furthermore, with limited cybersecurity resources, businesses need to prioritise their efforts to strengthen cyber posture effectively; however, many organisations do not have an anchor point or a guiding principle, to begin with. With cyber-intelligence inputs missing from cybersecurity capabilities like incident management, vulnerability management, risk assessment and brand monitoring, businesses end up running their security practice in silos instead of an integrated approach.

And, thus, in an attempt to revolutionise the cyber threat visibility and intelligence market, CYFIRMA, a cyber analytics startup assists businesses to understand the relevance of the current threat landscape. Not only it provides insights on threat actors and indicators, emerging threats and digital risks, but also automatically applies intelligence into cyber posture management. To dig deeper, Analytics India Magazine got in touch with the chairman and CEO of the company, Kumar Ritesh, to understand how the company uses a predictive intelligence-driven approach to discover cyber threats.

#startups #cyber security startup india #cybersecurity startup #machine learning #startup #startups

How to Monitor Third Party API Integrations

Many enterprises and SaaS companies depend on a variety of external API integrations in order to build an awesome customer experience. Some integrations may outsource certain business functionality such as handling payments or search to companies like Stripe and Algolia. You may have integrated other partners which expand the functionality of your product offering, For example, if you want to add real-time alerts to an analytics tool, you might want to integrate the PagerDuty and Slack APIs into your application.

If you’re like most companies though, you’ll soon realize you’re integrating hundreds of different vendors and partners into your app. Any one of them could have performance or functional issues impacting your customer experience. Worst yet, the reliability of an integration may be less visible than your own APIs and backend. If the login functionality is broken, you’ll have many customers complaining they cannot log into your website. However, if your Slack integration is broken, only the customers who added Slack to their account will be impacted. On top of that, since the integration is asynchronous, your customers may not realize the integration is broken until after a few days when they haven’t received any alerts for some time.

How do you ensure your API integrations are reliable and high performing? After all, if you’re selling a feature real-time alerting, you’re alerts better well be real-time and have at least once guaranteed delivery. Dropping alerts because your Slack or PagerDuty integration is unacceptable from a customer experience perspective.

What to monitor

Latency

Specific API integrations that have an exceedingly high latency could be a signal that your integration is about to fail. Maybe your pagination scheme is incorrect or the vendor has not indexed your data in the best way for you to efficiently query.

Latency best practices

Average latency only tells you half the story. An API that consistently takes one second to complete is usually better than an API with high variance. For example if an API only takes 30 milliseconds on average, but 1 out of 10 API calls take up to five seconds, then you have high variance in your customer experience. This is makes it much harder to track down bugs and harder to handle in your customer experience. This is why 90th percentile and 95th percentiles are important to look at.

Reliability

Reliability is a key metric to monitor especially since your integrating APIs that you don’t have control over. What percent of API calls are failing? In order to track reliability, you should have a rigid definition on what constitutes a failure.

Reliability best practices

While any API call that has a response status code in the 4xx or 5xx family may be considered an error, you might have specific business cases where the API appears to successfully complete yet the API call should still be considered a failure. For example, a data API integration that returns no matches or no content consistently could be considered failing even though the status code is always 200 OK. Another API could be returning bogus or incomplete data. Data validation is critical for measuring where the data returned is correct and up to date.

Not every API provider and integration partner follows suggested status code mapping

Availability

While reliability is specific to errors and functional correctness, availability and uptime is a pure infrastructure metric that measures how often a service has an outage, even if temporary. Availability is usually measured as a percentage of uptime per year or number of 9’s.

AVAILABILITY %DOWNTIME PER YEARDOWNTIME PER MONTHDOWNTIME PER WEEKDOWNTIME PER DAY90% (“one nine”)36.53 days73.05 hours16.80 hours2.40 hours99% (“two nines”)3.65 days7.31 hours1.68 hours14.40 minutes99.9% (“three nines”)8.77 hours43.83 minutes10.08 minutes1.44 minutes99.99% (“four nines”)52.60 minutes4.38 minutes1.01 minutes8.64 seconds99.999% (“five nines”)5.26 minutes26.30 seconds6.05 seconds864.00 milliseconds99.9999% (“six nines”)31.56 seconds2.63 seconds604.80 milliseconds86.40 milliseconds99.99999% (“seven nines”)3.16 seconds262.98 milliseconds60.48 milliseconds8.64 milliseconds99.999999% (“eight nines”)315.58 milliseconds26.30 milliseconds6.05 milliseconds864.00 microseconds99.9999999% (“nine nines”)31.56 milliseconds2.63 milliseconds604.80 microseconds86.40 microseconds

Usage

Many API providers are priced on API usage. Even if the API is free, they most likely have some sort of rate limiting implemented on the API to ensure bad actors are not starving out good clients. This means tracking your API usage with each integration partner is critical to understand when your current usage is close to the plan limits or their rate limits.

Usage best practices

It’s recommended to tie usage back to your end-users even if the API integration is quite downstream from your customer experience. This enables measuring the direct ROI of specific integrations and finding trends. For example, let’s say your product is a CRM, and you are paying Clearbit $199 dollars a month to enrich up to 2,500 companies. That is a direct cost you have and is tied to your customer’s usage. If you have a free tier and they are using the most of your Clearbit quota, you may want to reconsider your pricing strategy. Potentially, Clearbit enrichment should be on the paid tiers only to reduce your own cost.

How to monitor API integrations

Monitoring API integrations seems like the correct remedy to stay on top of these issues. However, traditional Application Performance Monitoring (APM) tools like New Relic and AppDynamics focus more on monitoring the health of your own websites and infrastructure. This includes infrastructure metrics like memory usage and requests per minute along with application level health such as appdex scores and latency. Of course, if you’re consuming an API that’s running in someone else’s infrastructure, you can’t just ask your third-party providers to install an APM agent that you have access to. This means you need a way to monitor the third-party APIs indirectly or via some other instrumentation methodology.

#monitoring #api integration #api monitoring #monitoring and alerting #monitoring strategies #monitoring tools #api integrations #monitoring microservices

Top Credit Scoring Startups In India That Use AI

Typically financial institutions ask the credit bureau to furnish a credit score of an individual for deciding whether an applicant should be given a loan based on the applicant’s ability to repay it. This is typically calculated using the borrower’s credit history.

There are many startups working on alternatives to design credit score models based on AI techniques to check the creditworthiness of individuals, especially those who may not have formal credit repayment history. There are many data points generated with a plethora of digital transactions that can provide important information about how people handle their financial obligations.

That’s where Indian fintech startups have come in to accelerate the credit economy by leveraging artificial intelligence-based credit assessment, working alongside banks, NBFCs and other financial institutions. In this article, we take a look at the leading fintech startups in India who do credit scoring by utilising advanced analytics and AI modelling.

#opinions #ai startup #credit score #credit scoring #startups #ai