Compare ModelOp vs. SurePath AI

Fully managed ML tools allow you to build, deploy and scale machine-learning (ML) models quickly, for any use case. Vertex AI Workbench is natively integrated with BigQuery Dataproc and Spark. You can use BigQuery to create and execute machine-learning models in BigQuery by using standard SQL queries and spreadsheets or you can export datasets directly from BigQuery into Vertex AI Workbench to run your models there. Vertex Data Labeling can be used to create highly accurate labels for data collection. Vertex AI Agent Builder empowers developers to design and deploy advanced generative AI applications for enterprise use. It supports both no-code and code-driven development, enabling users to create AI agents through natural language prompts or by integrating with frameworks like LangChain and LlamaIndex.

kama.ai's Designed Emotional Intelligence, kama DEI, truly understands the meaning and human impact behind your client or user's situation or inquiry the way we as people understand each other. Our Natural Language Understanding (NLU) technology, combined with our proprietary knowledge base, and our human value guidance algorithm supports true human-like understanding and inference behind the interactions with users. Our knowledge base content is easily 'programmed' in natural language, rated by human values, that we all understand, creating an ever expanding Virtual Agent that can answer questions for your clients, employees or other stakeholders. Conversation journeys deliver prioritized product and service information, directly the way your product or service experts or client practitioners want to communicate it. No data scientists or programmers are required. kama DEI Agents can 'speak' over our website chat interface, Facebook Messenger, smart speakers, or from within mobile applications. Ultimately, we help you get the right information, to the right people, at the right time, providing any-time client engagement, increasing your marketing ROI and building your brand's loyalty

DataHub is a versatile open-source metadata platform crafted to enhance data discovery, observability, and governance within various data environments. It empowers organizations to easily find reliable data, providing customized experiences for users while avoiding disruptions through precise lineage tracking at both the cross-platform and column levels. By offering a holistic view of business, operational, and technical contexts, DataHub instills trust in your data repository. The platform features automated data quality assessments along with AI-driven anomaly detection, alerting teams to emerging issues and consolidating incident management. With comprehensive lineage information, documentation, and ownership details, DataHub streamlines the resolution of problems. Furthermore, it automates governance processes by classifying evolving assets, significantly reducing manual effort with GenAI documentation, AI-based classification, and intelligent propagation mechanisms. Additionally, DataHub's flexible architecture accommodates more than 70 native integrations, making it a robust choice for organizations seeking to optimize their data ecosystems. This makes it an invaluable tool for any organization looking to enhance their data management capabilities.

Interfacing’s Integrated Management System (IMS ) is an AI-supported platform that brings BPM, QMS, Document Control, and GRC together in one environment. Teams use IMS to design and manage processes, govern documentation, oversee risks, and demonstrate compliance with complete visibility and reliable audit evidence. Built for sectors that depend on strict oversight, such as aerospace, life sciences, public sector, and financial services, IMS offers real-time monitoring, automated workflows, and AI-driven analytics that strengthen quality and lower operational exposure. The system is ISO 27001 certified and validated for 21 CFR Part 11, ensuring secure and compliant use in regulated operations. IMS also provides low-code automation, process mining, audit tools, training management, CAPA workflows, and dashboards that help organizations improve performance and maintain regulatory control. AI enhances governance, improves precision, and supports continuous compliance.

Introducing the pioneering monetization platform tailored for today’s billing ecosystem. This solution mitigates risks, enables concentration on core tasks, and enhances the variety of pricing and packaging alternatives while minimizing code requirements. Serving as a distinct middleware, a monetization platform integrates seamlessly between your application and your business tools, becoming an essential part of the contemporary enterprise billing framework. Stigg consolidates all the APIs and abstractions that billing and platform engineers would otherwise need to develop and maintain internally. By acting as your authoritative source of information, it offers robust and adaptable entitlements management, making the process of implementing pricing and packaging adjustments a straightforward, self-service task devoid of risk. With Stigg, engineers gain precise control over the components that can be priced and packaged individually. You can impose restrictions and manage your customers' commercial permissions at a feature level, simplifying intricate billing concepts within your code. Ultimately, entitlements represent the cutting-edge approach to software monetization, providing a versatile and adaptive framework for hybrid pricing strategies, ensuring businesses can thrive in a competitive landscape. This fresh approach not only streamlines billing processes but also empowers companies to innovate and respond to market demands quickly.

Accelerate your data journey with AnalyticsCreator—a metadata-driven data warehouse automation solution purpose-built for the Microsoft data ecosystem. AnalyticsCreator simplifies the design, development, and deployment of modern data architectures, including dimensional models, data marts, data vaults, or blended modeling approaches tailored to your business needs. Seamlessly integrate with Microsoft SQL Server, Azure Synapse Analytics, Microsoft Fabric (including OneLake and SQL Endpoint Lakehouse environments), and Power BI. AnalyticsCreator automates ELT pipeline creation, data modeling, historization, and semantic layer generation—helping reduce tool sprawl and minimizing manual SQL coding. Designed to support CI/CD pipelines, AnalyticsCreator connects easily with Azure DevOps and GitHub for version-controlled deployments across development, test, and production environments. This ensures faster, error-free releases while maintaining governance and control across your entire data engineering workflow. Key features include automated documentation, end-to-end data lineage tracking, and adaptive schema evolution—enabling teams to manage change, reduce risk, and maintain auditability at scale. AnalyticsCreator empowers agile data engineering by enabling rapid prototyping and production-grade deployments for Microsoft-centric data initiatives. By eliminating repetitive manual tasks and deployment risks, AnalyticsCreator allows your team to focus on delivering actionable business insights—accelerating time-to-value for your data products and analytics initiatives.

Everything works right here™. The product of years of collaboration with the world’s largest financial institutions, HERE Enterprise Browser is the first and only browser that solves both enterprise security and workforce productivity. Built on Google Chromium, HERE streamlines workflow and improves employee experience.

dbt Labs is redefining how data teams work with SQL. Instead of waiting on complex ETL processes, dbt lets data analysts and data engineers build production-ready transformations directly in the warehouse, using code, version control, and CI/CD. This community-driven approach puts power back in the hands of practitioners while maintaining governance and scalability for enterprise use. With a rapidly growing open-source community and an enterprise-grade cloud platform, dbt is at the heart of the modern data stack. It’s the go-to solution for teams who want faster analytics, higher quality data, and the confidence that comes from transparent, testable transformations.

Teradata VantageCloud: Open, Scalable Cloud Analytics for AI VantageCloud is Teradata’s cloud-native analytics and data platform designed for performance and flexibility. It unifies data from multiple sources, supports complex analytics at scale, and makes it easier to deploy AI and machine learning models in production. With built-in support for multi-cloud and hybrid deployments, VantageCloud lets organizations manage data across AWS, Azure, Google Cloud, and on-prem environments without vendor lock-in. Its open architecture integrates with modern data tools and standard formats, giving developers and data teams freedom to innovate while keeping costs predictable.

All stakeholder engagement activities can be managed from one platform. Additional modules can be added to strengthen governance, environment, and social areas. Borealis' Stakeholder Engagement module gives you the tools to create more effective engagement plans, strengthen relationships with stakeholders, and align processes with industry best practice. To simplify your day, the Stakeholder Engagement module centralizes all stakeholder information and makes it easily accessible. Build stakeholder trust with a proven methodology Plan Connect engagement strategy to execution. The mapping tool in Borealis makes it easy to analyze stakeholders to prioritize the allocation of resources. Engage Communicate with stakeholders in a more relevant and timely manner. Borealis uses AI-driven machine learning to keep records clean and up-to-date. Measure Prove compliance with ever-evolving standards. Borealis lets you easily track and progress, generate reports and documentation, and demonstrate the impacts of your efforts.