Case Study: Anodot Helps Netseer See Results

NetSeer provides market leading visual monetization solutions for advertisers and publishers backed by its patented ConceptGraph™ intent engine. The company’s InImage advertising solution is changing the game in the industry as it delivers exceptional performance across desktop, mobile, and video inventory. As a leading adtech company, Netseer sees a large portion of internet traffic and…

Meetup: Real-Time Business Incident Detection with Machine Learning

Delayed business insights cost companies millions of dollars. Data-centric companies like Web-based businesses, AdTech, FinTech and IoT face unique challenges because it is impossible to manually track the millions of metrics that are generated in today’s digital businesses. Static thresholds for seasonal data are either meaningless or cause alert-storms. So…what can we do? This was…

Fintech Companies Gain Reliability Through Business Incident Detection

Financial Technology companies process transactions and lend funds in greater quantities than ever before, and they are initiating new financial business models. These money-oriented businesses need 100% uptime, and their success is predicated on a consumer perception that they are as reliable as, say, the dial tone. If an online payment or loan request suddenly hangs…

Presidential Debate Redux – For Trump, Lots of Russia, Not Much Support

We’ve been tracking the elections with our own business incident detection solution for the past several weeks, and it’s been so interesting to see the day to day elements of the campaigns such as debates or key news stories affect certain metrics. As I explained in this previous post, we have been using the word “donate” together with…

Webinar October 13: Accurate Anomaly Detection with Machine Learning

Achieving accurate anomaly detection requires more than statistics. Simple assumptions like normal distribution do not work in the real world. Time series data – representing anything from customer acquisition, to application performance, to manufacturing KPIs – tend to have many different behaviors that need to be modeled accurately. These include seasonal patterns, non-stationary behaviors, and…

Who Won the Debates? It’s All in the Anomalies…

With two debates behind us, the first presidential debate and the vice presidential debate, public discussion has swirled around the question of who won, and what impact did it have? Since these are not the rigorously judged debates of the high school/college debate circuit, winners may be determined by pundits, by polls, or even by the candidates themselves. We…

Anodot Secures $8M in Funding

We’ve been working so hard and are so excited to be able to share that we have raised $8 million in funding led by Aleph Venture Capital with participation by Disruptive Technologies L.P.. This brings our total funding to $12.5 million, and we couldn’t be happier. These funds will go straight towards our efforts to serve our customers better. We…

New Features Make the Anodot Experience Even Better

The Anodot elves have been busy in the workshop, building new features to improve Anodot results and user experience. Over the last few weeks, we have rolled out the following new features: Events We introduced an “Events” feature to help you create a timeline of milestones and events including deployment, holidays and occasional alerts that may affect the behavior…

Single Sign On Available for Anodot via SAML

You asked for it, you got it – now it’s possible to sign in to Anodot with your corporate credentials. Anodot supports SAML (Security Assertion Markup Language), an XML-based, open-standard data format for exchanging authentication and authorization data, in particular, between an identity provider and a service provider. Configuring SAML for your Anodot account will…

Seven Lessons To Get You Through the First Two Years in a Startup

It feels like just yesterday we painted the walls of our office and started our journey of building Anodot, a machine learning SaaS platform for detecting business incidents in real time at massive scale. Since that day, two years ago, we’ve learned many lessons as we’ve grown our company. Lesson 1: Superstitions can help you…

How Outlier Detection Saved our Cassandra Cluster

In most SaaS applications – and Anodot is no different – the software stack consists of multiple cluster components that scale in or out depending on the need. Monitoring the cluster, and in particular issue tracking, becomes more challenging as the cluster grows: while it possible to monitor each node on a 10-node cluster in…

Learning the Learner: The Ultimate Way to Monitor Machine Learning

The machine learning process can be summarized in five major steps as illustrated below: Define the business problem Collect and prepare data Train and test model Deploy model Monitor model’s performance The diagram to the right illustrates how the steps feed into each other into a cycle. Most available data science tools put a lot of…