DRIVING AI-POWERED, SIMPLIFIED
AND AUTOMATED HYBRID CLOUD

Self managed & self healing from the core to the edge
through preventive maintenance and automated mitigation

DRIVING AI-POWERED, SIMPLIFIED AND AUTOMATED HYBRID CLOUD MONITORING

Self managed & self healing from the core to the edge
through preventive maintenance and automated mitigation

We Are Next Gen-AIOps

Sensai provides an AI based anomaly detection, root cause analysis and prediction tool, enabling real time resolution of issues.
Our success is when Hybrid Cloud managers reduce the frequency and duration of downtime.

We Are Next Generation AIOps

Sensai provides an AI based real time anomaly detection, diagnosis and prediction tool, enabling real time resolution of issues.
We optimize hybrid cloud performance, reduce frequency and duration of outages, ensuring your SLA compliance.

Integrated View

  • SaaS-based hybrid cloud monitoring 
  • Empowers CIOs to manage SLAs for improved performance and profitability
  • Streamlines & automates anomaly detection, prediction, root cause analysis (RCA) & resolution
  • Eliminates heavy manual root cause analysis process
  • Empowers I&O leaders and NOC managers to solve complex issues faster
  • Constantly evolving AI capabilities

  • Holistic view & integrated analytics through integration w/3rd party tools

Integrated View

  • SaaS-based data center monitoring 

  • Empowers CIO to manage SLAs for improved performance and profitability

  • Streamlines & automates anomaly detection, prediction, debugging & resolution

  • Eliminates heavy manual intervention due to disconnect between detection & debugging

  • Empowers NOC operators to solve complex issues faster

  • Constantly evolving AI capabilities

  • Holistic view & integrated analytics through integration w/3rd party tools

How it works

DETECT ANOMALIES

Done in real time, using metrics and not After the fact, using logs

ROOT CAUSE ANALYSIS

Automatically generated at time of detection and not manually initiated as traditional processes through creating separate processes and combination of different tools

MITIGATION

Automated, towards self-managed, self-healing from the buttom up. Eliminating manual work that requires excessive redundancies to buy time to resolution

PREDICT ANOMALIES

Self-learned based on trigger root causes not sporadic or using selected logs & anomalies

Who are we?

Hanadi Said

Co-founder & CEO

Rafi Horev

SVP R&D

Moti Elkayam

Director Product & Bus. Dev.

Inas Said

Co-founder & chairman of the BOD

Yoram Yaacovi

Board member

Advisors

Bar Vinograd

Advisor

Alex Balk

Advisor

The Art Of Working As A Site Reliability Engineer (SRE)
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We are hiring

If you wish to join our team, please email your CV to info@sensai.io

Sales & Marketing | Job ID: 4-2020

About Sensai

Sensai is on a mission to develop the best Real-Time AI powered anomaly prediction tool for data centers & Cloud solutions as an essential element in the data center automation process & SLA monitoring.

If you enjoy working in a startup but want to sell a product with a huge community of customers globally come help us sell the next generation of intelligent, automated monitoring & troubleshooting tools.

At Sensai, we are committed to our work, customers, having fun and most meaningfully to each other’s success.

Responsibilities

The ML team leader’s job is to design and develop the cognitive core (encompassing multiple models) of a software based active monitoring tool which monitors, analyses and predicts behaviors in a Hybrid Cloud environment, taking it from concept to launch.

Lead, collaborate and work efficiently amongst a team of developers, designers and consultants. Work very closely with the system infrastructure and UI teams to build AI based projects from start to finish. The candidate is expected to know and adapt to leading technologies and to work hands-on. The ML team leader is expected to provide leadership to the ML team to develop efficient code and to create infrastructure to support team’s algorithmic development goals.

We are looking for someone who is passionate about problem-solving, has proven experience developing ML models in production at scale, a strong theoretical background, and proven experience leading data science teams.

Skills and Qualifications

  • MS.C or Phd. in Computer Science, computer Engineering, Mathematics, Statistics, other technical sciences.
  • 5+ years of experience ML production grade software – MUST
  • At least 3 years’ experience as an ML project/team leader
  • Strong theoretical and practical background in a variety of machine learning techniques, including unsupervised learning.
  • Knowledge in causality – Advantage.
  • Knowledge of ML system design, and with ML main algorithms.
  • Experience in a fast-paced development environment, and an ability to execute against aggressive timelines.
  • Highly creative and inquisitive; able to multitask effectively; embraces challenges and is a true team player.
  • Working with Python, Java, TensorFlow.

Advantage

  • Knowledge with big data, NoSQL, Elastic search, Spark
  • Experience in startup environment
  • Hybrid Cloud industry experience
  • Networking experience

R&D | Full Time | Job ID: 2-2020

About Sensai

Sensai is on a mission to develop the best Real-Time AI powered anomaly prediction tool for data centers & Cloud solutions as an essential element in the data center automation process & SLA monitoring.

As a Senior Software Engineer at Sensai you will join the Infrastructure team, envision, build, deploy and develop a breakthrough AI driven Data Center Monitoring Platform with a new innovative approach.

At Sensai, we are committed to our work, customers, having fun and most meaningfully to each other’s success.

Responsibility

  • Executing projects end-to-end from requirements gathering, data mining and exploration up to implement machine learning algorithms.
  • Work closely with R&D, product team to design, deploy and evaluate ML models and optimization algorithms.
  • Identify and decide on promising research and development directions, balancing short term and long-term goals.
  • Communication and coordination with product and business counterparts.

Skills and Qualifications

  • Sc. or Ph.D. in Computer Science/Statistics/Engineering or related field with a focus on applied statistics, AI, machine learning.
  • At least 4 years of working experience in the field of data science / machine learning – MUST.
  • At least 4 years programming experience in Python – MUST.
  • Experience in developing deep learning models with TensorFlow, Keras, or other common frameworks – MUST.
  • Experience with predictive and probabilistic models, clustering algorithms, classification models for multivariate time series data.
  • Self-learner, strong can-do attitude and great interpersonal skills.
  • Hands-on problem solver fit for dynamic start-up environment.

Advantages

  • Experience in startup environment
  • Cloud & Data center industry experience
  • Networking experience

R&D | Full Time | Job ID: 1-2020

About Sensai

Sensai is on a mission to develop the best Real-Time AI powered anomaly prediction tool for data centers & Cloud solutions as an essential element in the data center automation process & SLA monitoring.

If you enjoy working in a startup then join us to develop a challenging simulated network environment which can generate effective data that helps build the next generation of intelligent, automated monitoring & troubleshooting tools.

At Sensai, we are committed to our work, customers, having fun and most meaningfully to each other’s success.

Responsibilities

  • Design and develop the infrastructure for state of the art, large scale, real-time predictive AI-system based on machine learning algorithms and big data.
  • Lead the design and development of automated data and machine learning pipelines.
  • Responsible for the experimentation infrastructure and reducing the time and effort of transforming experiments to production-ready models.
  • Interact with other teams to define interfaces and understand and resolve dependencies.
  • Implement model usages from research to production, in a scalable and resilient architecture (and be part of creating and maintaining this architecture).

Skills and Qualifications

  • in Computer Science/ Software Engineering, MSc. is an advantage.
  • 4+ years of Software Engineer experience with Python and building production-grade products.
  • 2+ years of experience in the field of machine learning and deep learning.
  • Experience with machine-learning frameworks (Sklearn/Tensorflow/Keras/Pytorch etc) – advantage
  • Experience with MLOPS and tools (AutoML / Vertex …) – advantage.
  • Experience in development of resource-intensive, high-concurrency applications – advantage.

Advantage

  • Experience in startup environment
  • Cloud & Data center industry experience
  • Networking experience

Contact us

Please fill your personal details at the contact form below and one of our representatives will be happy to get back to you as soon as possible.