AI for Managing IT

Devops is struggling to keep up. Web architectures are complex and fluid, creating an accelerating stream of real-time operational problems that have immediate revenue impact. What is needed is automation that can predict and remediate problems before they occur. Based on radical AI technology developed at Stanford University NMLStream's products give Devops the predictive automation they require, thereby accelerating Devops and protecting revenue.

Our solution is automatic, predictive and pro-active, whether used in the cloud, on-prem or in hybrid systems. It presents DevOps with an integrated prediction oriented management view of applications and system performance. NMLStream’s augmented intelligence approach recommends actions and, if appropriate, can execute these actions. Our technology generates a common digital language of system’s behaviors, simplifies collaboration across IT silos.


NMLStream's technology and platform address pressing management challenges across a wide range of markets. NMLStream's platform represents an automated Managment Intelligence solution for industries overwhelmed by big streaming data and tightening decision loops. In the following industries, recent trends have made Management Intelligence imperative:

Enterprise IoT

Comprehensive instrumentation and monitoring has overloaded manual operator decision-making. Mangement Intelligence makes automated data-driven decisions based on millions of sensor values per second possible.

Software Defined Networking

As virtualization penetrates all layers of the datacenter, abstraction introduces complexity. Management Intelligence is necessary to maintain performance and reliability in a constantly changing system.

IT Admin & DevOps

Business demands require shifting to a hybrid cloud model and custom applications with countless interacting systems and people. Only Management Intelligence ensures availability in complex environments.
In asset intensive businesses, revenue is tied directly to equipment uptime. With compehensive monitoring, operators are subject to more equipment alarms than ever before. Each alarm requires substantial manual triage, inspection, and resolution. However, standard monitoring techniques are vulnerable to false alarms, which expend operator resources and result in unplanned downtime. NMLStream's Managment Intelligence has demonstrated over 40% improvement in false alarm rates.
Application Delivery Controllers (ADCs) shape network traffic for performance, reliability, and security. However, they require extensive configuration based on the characteristics of the application, current load, and network topology. In a Software Defined Network, all of these factors change rapidly, making manual reconfiguration prohibitively expensive. NMLStream's Managemenent Intelligence can reconfigure ADCs in response to changing system conditions much faster than humans, reducing the burden for IT administrators.
When custom applications directly impact revenue, keeping them online is essential. However, they are difficult to maintain because documentation is scarce, and knowledge is distributed between developers who may no longer be available. NMLStream's Management Intelligence is able to learn the characteristics of custom applications without examining or modifying the code. With this automatic centralized understanding, triaging and resolving issues becomes orders of magnitude more efficient.


Increased System Uptime

Knowledge Standardization

Accurate and Early Warnings

Optimized Performance

System Automation

Fast Issue Resolution


NMLStream's Management Intelligence works with business critical systems and users at all levels in the organization. Administrators effortlessly apply automated decision policies. Managers evaluate the performance of these policies over time, enabling steady operational improvement. Executives obtain a comprehensive and immediate understanding of how the critical elements of their businesses behave, allowing timely response to changing business demands.

Business Agility

Operational Excellence

Pervasive Automation

NMLStream Management Intelligence
MLStream Management Intelligence
Infrastructure Monitoring Platform
Business Infrastructure and Applications

NMLStream's Management Intelligence sits on top of monitoring platforms, tying together machines and DevOps with adaptive intelligence that learns rapidly over time. NMLStream's platform is built to handle growing complexity and deploy effortlessly regardless of the customer's configuration with its modern stack: Apache Spark, Node.js, HTML5. For a product demo contact us.


NMLStream's proprietary technology was developed at Stanford. It rapidly condenses large quantities of complex streaming data into succinct summaries without manual data science. These summaries provide the robust system representation necessary for automated decision making. For a detailed discussion of NMLStream's technology and its relationship to existing techniques contact us.

Streaming Data

Behavior Summary

Automated Action

Founding Team

Dan O'Neill


Assistant Professor Research

Sr. Director
SUN Microsystems

GM and Director
Texas Instruments


Sachin Adlakha

Chief Data & Analytics Officer

Sr. Data Scientist

Software Engineer
Texas Instuments


Peter Pham

VP of Engineering

Sr. Algorithms Developer


Job Openings

VP of Product Management

  • Manage flagship product and partner strategy
  • Engage with customers and act as customer proxy in product development
  • Manage market messaging, pricing strategy, and product delivery process
  • Engineering degree and MBA
  • 10+ years of experience including startup experience

Front End Software Engineer

  • 2+ years of software development experience
  • Working knowledge of NodeJS, ReactJS, MeteorJS, Web Standards
  • Familiarity with standard development processes
  • Good written and verbal comunication skills
  • BS/BA in CS, EE, or related field

Full Stack Software Engineer

  • 2+ years of software development experience
  • Working knowledge of JS, NodeJS, MongoDB, cloud application deployment
  • Familiarity with standard development processes
  • Good written and verbal comunication skills
  • BS/BA in CS, EE, or related field

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