Nexla

About Nexla

The startup offers a converged data platform that enables real-time inter-company data collaboration through a no-code and low-code interface for data integration, preparation, cataloging, and exchange. This platform provides organizations with reliable access to consistent data, enhancing decision-making and operational efficiency across internal and external stakeholders.

```xml <problem> Organizations struggle to efficiently integrate, prepare, and exchange data across internal and external systems, leading to inconsistent data access and delayed decision-making. Traditional data integration processes often require extensive coding and specialized expertise, creating bottlenecks and hindering real-time data collaboration between companies. This complexity increases data engineering costs and reduces agility in responding to changing business needs. </problem> <solution> Nexla offers a converged data integration platform that simplifies real-time, inter-company data collaboration through a no-code/low-code interface. The platform provides tools for data integration (ETL/ELT/R-ETL), data preparation, data cataloging, and data exchange, enabling organizations to access consistent, ready-to-use data. Nexla's metadata-driven approach allows users to connect to any data source or destination, integrate data in any style, and deliver data at any speed. The platform supports both pro-code and no-code users, fostering cross-functional collaboration and reducing data engineering costs. Nexla also provides advanced support for GenAI, including RAG, multi-LLM models, and multi-modal data integration. </solution> <features> - No-code/low-code interface for data integration, preparation, and exchange - Support for ETL, ELT, and R-ETL integration patterns - Real-time data streaming and change data capture (CDC) capabilities - API integration (iPaaS and data API) - Data fabric architecture for unified data management across on-premises and cloud systems - Nexsets for virtual data product creation and management - Enterprise-grade security, compliance, and governance features - Advanced RAG support for agentic, multi-LLM models - GenAI ETL integration for multi-modal, structured, and unstructured data - Comprehensive data monitoring, notifications, and error management </features> <target_audience> The primary target audience includes data engineers, data architects, data scientists, and business analysts in enterprises across various industries such as finance, retail, healthcare, and asset management, who need to integrate and share data efficiently for analytics, operations, and AI/GenAI initiatives. </target_audience> ```

What does Nexla do?

The startup offers a converged data platform that enables real-time inter-company data collaboration through a no-code and low-code interface for data integration, preparation, cataloging, and exchange. This platform provides organizations with reliable access to consistent data, enhancing decision-making and operational efficiency across internal and external stakeholders.

Where is Nexla located?

Nexla is based in San Mateo, Philippines.

When was Nexla founded?

Nexla was founded in 2016.

How much funding has Nexla raised?

Nexla has raised 33570000.

Location
San Mateo, Philippines
Founded
2016
Funding
33570000
Employees
86 employees
Major Investors
Shield Capital

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Nexla

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Executive Summary

The startup offers a converged data platform that enables real-time inter-company data collaboration through a no-code and low-code interface for data integration, preparation, cataloging, and exchange. This platform provides organizations with reliable access to consistent data, enhancing decision-making and operational efficiency across internal and external stakeholders.

nexla.com3K+
cb
Crunchbase
Founded 2016San Mateo, Philippines

Funding

$

Estimated Funding

$20M+

Major Investors

Shield Capital

Team (75+)

No team information available.

Company Description

Problem

Organizations struggle to efficiently integrate, prepare, and exchange data across internal and external systems, leading to inconsistent data access and delayed decision-making. Traditional data integration processes often require extensive coding and specialized expertise, creating bottlenecks and hindering real-time data collaboration between companies. This complexity increases data engineering costs and reduces agility in responding to changing business needs.

Solution

Nexla offers a converged data integration platform that simplifies real-time, inter-company data collaboration through a no-code/low-code interface. The platform provides tools for data integration (ETL/ELT/R-ETL), data preparation, data cataloging, and data exchange, enabling organizations to access consistent, ready-to-use data. Nexla's metadata-driven approach allows users to connect to any data source or destination, integrate data in any style, and deliver data at any speed. The platform supports both pro-code and no-code users, fostering cross-functional collaboration and reducing data engineering costs. Nexla also provides advanced support for GenAI, including RAG, multi-LLM models, and multi-modal data integration.

Features

No-code/low-code interface for data integration, preparation, and exchange

Support for ETL, ELT, and R-ETL integration patterns

Real-time data streaming and change data capture (CDC) capabilities

API integration (iPaaS and data API)

Data fabric architecture for unified data management across on-premises and cloud systems

Nexsets for virtual data product creation and management

Enterprise-grade security, compliance, and governance features

Advanced RAG support for agentic, multi-LLM models

GenAI ETL integration for multi-modal, structured, and unstructured data

Comprehensive data monitoring, notifications, and error management

Target Audience

The primary target audience includes data engineers, data architects, data scientists, and business analysts in enterprises across various industries such as finance, retail, healthcare, and asset management, who need to integrate and share data efficiently for analytics, operations, and AI/GenAI initiatives.

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