Convex is a no-code analytics orchestration platform designed to accelerate and democratize advanced analytics and predictive modeling processes at an enterprise scale. The platform enables users to design, deploy, and sustainably manage high-performance predictive models in operational environments without requiring technical expertise.

In traditional development approaches, the dependency on developers and data scientists led to time-consuming model development cycles, operational bottlenecks, and limited user accessibility, preventing analytics capabilities from being scaled across the organization. With Convex, it was targeted that analytics development processes would be standardized end-to-end, business units would be directly involved in the process, and the model lifecycle would be managed in a controlled and scalable manner at an enterprise level.

Industries & Roles

The platform is positioned for data science teams, risk and credit governance units, business analytics departments, operations and customer management functions, as well as business professionals who leverage analytics as a decision-support capability. It is designed to create value for both technical and non-technical user profiles.

 

Why Convex?

The platform stands out with its no-code approach that democratizes analytics development processes, its governance-aligned architecture, and its rapid deployment capability. Additionally, through its integrated structure that minimizes the gap between model development and operational usage, it enables organizations to strengthen and sustain their enterprise analytics maturity.

Features

  • No-Code Model Development and Data Preparation Fabric

    All core analytics and modeling workflows — including data ingestion, preprocessing, sampling, synthetic data generation, and feature engineering — are executed through fully no-code, guided interfaces, ensuring rapid delivery without requiring programming effort or specialist engineering capability.

  • Model Development and Feature Engineering Ecosystem

    Through automated and semi-automated feature engineering flows, advanced variable elimination and validation processes, performance-driven feature selection, and an auditable model lifecycle, the platform institutionalizes scalable and repeatable model development practices.

  • Governance, Security, and Compliance-Driven Architecture

    With robust access control, traceable process execution, auditable operational history, and alignment with enterprise security and governance policies, the platform mitigates operational risk and reinforces data stewardship discipline.

  • Operational Efficiency and Business Continuity Automation

    End-to-end workflow automation, reusable pipeline structures, and a centralized collaborative workspace reduce delivery lead times, increase operational throughput, and establish a sustainable, productivity-oriented analytics operating model.

Related Frequently Asked Questions

Does Convex require technical expertise to use?

Convex has been designed with a no-code approach and delivers a user experience that significantly reduces the need for technical expertise. While the corporate standards defined by data science teams are preserved, business units are enabled to directly contribute to analytics processes.

How is model performance and accuracy monitored?

Built-in mechanisms are provided for model versioning, performance tracking, and historical comparison. Model performance is monitored on an ongoing basis from the perspectives of operational outcomes, temporal stability, and business impact, and is reported within the governance framework.

How is production deployment of models managed?

Convex standardizes the entire transition from model development to production deployment. Go-live activities are executed in alignment with corporate change-management policies through approval workflows, control checkpoints, and secure transition steps.

How does Convex create value for both technical and non-technical users?

While standardized development and governance workflows are provided for technical users, business units gain the ability to directly participate in analytics processes and generate insights more rapidly. In this way, analytics capabilities are disseminated across the organization in a scalable manner.

Does the platform support synthetic data generation?

Yes, Convex supports synthetic data generation and enables the creation of artificial datasets that replicate the statistical characteristics of real-world data.

How does the data sampling feature work?

Convex allows both automatic and manual sampling across datasets. This capability is used for reducing large datasets, balancing imbalanced classes, or creating controlled subsets for testing purposes.