“Neu.ro MLOps decreased our NLP development time by more than 50%.”

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Sviatoslav Lobach
VP of Product Revenue Grid
Client gartner award
Revenue Grid is a global leader in AI-powered Guided Sales, prompting for missing activity, coaching in the moment and flagging managers ahead of risk for 25,000 clients worldwide including Honeywell, Lufthansa and Volvo.
CRM / AI-driven Guided Selling
State-of-the-art NLP :
Automated Text Clusterization and Sentiment Analysis

Developed and deployed entirely 
within the client’s secure Azure environment

>50% reduction in the client’s AI development time


Current State of CRM:1

$56.6 billion
Global CRM Market (2019)
Y-o-Y Growth (2018-2019)
SaaS as % of the CRM market
Revenue Grid is at the forefront of CRM market transformation from legacy products to AI-driven sales solutions powered by predictive analytics. They call this approach Guided Selling.2

Next Level CRM: AI-Driven Guided Selling

The global CRM industry continues its strong growth trajectory around the world. In the past, CRM software companies won customers by offering more effective streamlining of the sales process and maintaining better, easier-to-use records of contacts, customer interactions and sales team performance.

“By 2020, 30% of all B2B companies will employ some kind of AI to augment at least one of their primary sales processes.”                            -Gartner Research 

Today, deep learning is driving an AI Transformation of CRM. Algorithms are now able to derive intelligence from vast amounts of data that are created over the lifetime of customer interactions. What was primarily a passive tool for scheduling and record keeping is becoming a productivity multiplier for sales teams.

1 Gartner CRM Worldwide May 2020
2 Also known as Sales Intelligence, Revenue Intelligence, Sales Enablement 2.0
After a thorough evaluation of the market, Revenue Grid turned to Neu.ro.


Like many AI-focused companies, Revenue Grid had relied 
on in-house resources and personnel to develop AI solutions as well as manage the physical environments and toolsets required across the entire ML Lifecycle.

In mid-2020, Revenue Grid found themselves developing multiple new ML products simultaneously, stretching the capacity of their internal team. As these projects scaled, the company recognized that their aggressive GTM plan could face significant delays.

To de-risk delivery, Revenue Grid sought specialist outside resources to develop and deploy a new ML feature – specifically an ML-automated system for analyzing large volumes of emails, extracting target features, and providing insights based on the results.

Revenue Grid had several important parameters for evaluating vendors, including:

  • A seamless collaboration of internal and vendor teams
  • Data security
  • Co-location of data with existing Azure GPU cloud resources

After a thorough evaluation based on these parameters, Revenue Grid turned to Neu.ro.

State-of-the-art NLP:

Automated Text Clusterization and Sentiment Analysis
Developed and deployed entirely 
within the client’s secure environment in Azure cloud

>50% reduction in the client’s AI development time


Using the Neu.ro Platform and the state-of-the-art ML technologies, Neu.ro deployed an end-to-end solution into production within 45 days.

Neu.ro began the process by installing the Neu.ro MLOps Platform directly into Revenue Grid’s development environment on Azure Cloud. Within days, the two teams seamlessly collaborated, securely sharing all project assets and co-locating training data with Revenue Grid’s Azure-based NVIDIA GPU computational resources. This allowed the teams to protect sensitive data without circumventing the company’s existing security measures.

Once the MLOps platform was installed, Neu.ro was able to build an entire ML pipeline for the client, including data management, model development, model training, and deployment.

The pipeline included developing a custom automated data-labeling system that allowed for the identification and categorization of target features within email threads. Neu.ro used a state-of-the-art NLP algorithm that was subsequently trained, tuned, and tested with the data extracted. Finally, Neu.ro deployed the model within the Revenue Grid environment, where it continues to learn on the company’s real-time inference data.

In 45 days, Neu.ro was able to:

  • Develop and deploy entirely within the client’s secure Azure cloud environment
  • Provide a customized model based on the latest state-of-the-art research in deep learning
  • Reduce Revenue Grid’s development time by over 50%