How Elevatus Uses Neptune to Check Experiment Results in 1 Minute
Customer Company Size
SME
Region
- Middle East
Country
- Saudi Arabia
Product
- Neptune
- Google Cloud Storage
- PyTorch Lightning
- Optuna
- Kubernetes
Tech Stack
- Google Cloud
- Oracle Cloud
- Terraform
- Python
- FastAPI
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Digital Expertise
- Innovation Output
- Productivity Improvements
Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Predictive Analytics
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Software
- Professional Service
Applicable Functions
- Product Research & Development
- Business Operation
Use Cases
- Machine Condition Monitoring
- Remote Asset Management
Services
- Software Design & Engineering Services
- System Integration
About The Customer
Elevatus is a talent management platform headquartered in Riyadh, Saudi Arabia, with a focus on covering the entire pre-HR cycle of recruitment, hiring, and onboarding. The company operates within the Software & Technology industry and employs between 11 to 50 people. Elevatus is known for its innovative approach to simplifying hiring processes through intelligent systems. The platform's Video Assessment product allows applicants to apply via a one-way interview, showcasing its commitment to reducing complexity in recruitment. The company's Innovation department plays a crucial role in developing systems that cater to client needs, emphasizing the importance of seamless integration and user-friendly solutions. Elevatus's dedication to innovation and efficiency is evident in its approach to managing machine learning models and optimizing recruitment processes.
The Challenge
The team at Elevatus faced significant challenges in managing their machine learning models due to the lack of an observability layer. This absence led to inefficiencies, such as the need to reanalyze data and reimplement workflows whenever evidence for language models was requested. The team recognized the necessity of a mature observability layer to facilitate large-scale training jobs and involve stakeholders in auditing AI systems. They sought a model tracking solution that could provide historical performance tracking and integrate well with their existing tools, such as PyTorch Lightning and Optuna. The goal was to enhance model performance tracking and optimize compute utilization, enabling quick iteration across experiments.
The Solution
To address the challenges faced, Elevatus integrated Neptune into their workflow as a model tracking solution. This integration allowed the team to monitor functional and operational processes post-training script execution. Neptune's configuration was hardcoded into their YAML manifest file, enabling seamless tracking of model performance over time. The solution provided a centralized view for the team, facilitating better model evaluation, compute utilization optimization, and rapid iteration across experiments. With Neptune, the team could scale experiment monitoring as dataset sizes grew, ensuring no computational bottlenecks. The customizable user interface offered by Neptune allowed the team to design their own metrics and dashboards, enhancing their ability to visualize training and conduct in-depth investigations. This flexibility empowered the team to achieve significantly better results, with Neptune serving as a crucial component in their machine learning operations.
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
SET Creative Ditches Google Vault for Datto Backupify
When Kienholz first started at SET, the staff was using Microsoft Outlook for email with no form of data backup. It became apparent that something needed to change as the staff was often burdened with trying to recover emails from departed employees. Kienholz transitioned the team to Google’s Gmail and implemented Google Vault for backup purposes. While SET employees quickly adjusted to Gmail, which many use for personal email, the same could not be said for Google Vault. “Unlike most Google products, Vault was not user friendly at all. It’s very hard to search for items. We never really figured out how to do a restore either,” explained Kienholz. Due to SET’s work with high-profile brands, projects often go through many rounds of revisions right down to the eleventh hour. This means that every bit of information - especially data living in project managers’ emails - is crucial to delivering clients a polished design at deadline.
Case Study
Infosys achieves a 5–7 percent effort reduction across projects
Infosys, a global leader in consulting, technology, and outsourcing solutions, was facing significant challenges in application development and maintenance due to its distributed teams, changing business priorities and the need to stay in alignment with customer needs. The company used a mix of open source, home-grown and third-party applications to support application development projects. However, challenges resulting from distributed teams using manual processes increased as the company grew. It became more and more important for Infosys to execute its projects efficiently, so they could improve quality, reduce defects and minimize delays.
Case Study
Arctic Wolf Envelops Teamworks with 24x7 Cybersecurity Protection and Comprehensive Visibility
Teamworks, a leading athlete engagement platform, faced rising cyberthreats and needed enhanced visibility into its network, servers, and laptops. With software developers connecting from all over the world, the company sought to improve its security posture and position itself for future growth. The company had a secure platform but recognized the need for a more proactive solution to identify gaps within its technology infrastructure. Data exfiltration and malicious access were top concerns, prompting the need for a comprehensive security upgrade.
Case Study
Sawback IT and Datto Save Client From a Costly Mistake
Ballistic Echo, a software development house, faced a critical challenge when human error led to the deletion of thousands of lines of unique code. This incident occurred before the code was pushed to source control, resulting in significant loss of time, revenue, and work. The previous file-level backup solution they used was slow and inefficient, making it nearly impossible to manually recreate the lost work. The need for a more reliable and efficient business continuity solution became evident to avoid such disasters in the future.
Case Study
Opal Helps Customers Shine Thanks to Datto
SP Flooring & Design Center faced a ransomware attack that encrypted and locked their files. The attack was initiated through a compromised service account set up by an outside vendor. The ransomware infection was isolated quickly, but there was a concern about the extent of the data at risk. The company had backups in place but was unsure of how much information was compromised. The situation required immediate action to prevent further damage and restore the affected data.
Case Study
Zapier Aggregates Multiple Analytics in a Single Dashboard with the New Relic Platform
Zapier, a company that enables non-technical users to push data between hundreds of web applications, was facing a challenge in automating and provisioning servers for optimal performance. The company's environment consisted of 50 Linux servers on the Amazon Elastic Compute Cloud (EC2), a Django application split across several servers, and a backend consisting of a dynamic number of celery task workers fed by messages published to a RabbitMQ cluster. They also maintained a number of internal web services on nginx in front of Gunicorn and Node.js processes. Redis handled simple key and value stores, with logging handled by Graylog2 and ElasticSearch. However, they realized that no level of automation would be sufficient without an effective monitoring solution in place. They needed a tool that could provide immediate alerts when something was breaking and could be easily implemented into their environment.
