Revolutionary AI Low-Code Data Processing & Automation Platform for Digital Transformation

Enterprises today face mounting challenges from legacy systems, fragmented data silos, and complex integration issues that slow down digital and AI initiatives. This AI-powered automation platform transforms integration from a technical bottleneck into a strategic accelerator, enabling organizations to unlock trapped data assets worth billions.

By automating up to 70% of manual coding, the platform accelerates processing speeds by up to 10x while reducing operational costs. Its visual drag-and-drop interface democratizes data access, addressing the $5.5 trillion global skills gap by removing the need for specialized coding expertise. Enterprises can cut data preparation efforts from 80% to 20% of project cycles, connecting legacy mainframes seamlessly with modern cloud applications.

The urgency is clear: the data integration market is projected to reach $47.6 billion by 2034, yet 95% of IT leaders cite integration as the main barrier to AI adoption. Meanwhile, silos cost enterprises hundreds of thousands annually, and up to 80% of data projects fail due to poor preparation.

This platform empowers organizations to process millions of records in minutes across hybrid, cloud, and on-premises environments. Early adopters already report 171–295% ROI within three years, six-month payback periods, and over $2.4 million in productivity gains. With 70% of new applications expected to leverage low-code/no-code by 2026, this solution positions enterprises to lead the next wave of intelligent automation.

1. Low-code visual interface — drag-and-drop workflow designer for ETL (Extract, Transform, Load) without heavy coding.

2. Broad connectivity — supports diverse data formats and protocols for integration with:

• Legacy mainframe systems (IBM IMS, DB2, VSAM, CICS)
• Modern databases
• Cloud services
• APIs
• IoT devices

3. Flexible deployment options — on-premises, private cloud, public cloud, or hybrid; containerized on Kubernetes for easy scaling and management.

4. Unified real-time computing architecture — includes:

• Event message storage
• Operational logic management
• Built-in data monitoring
• Real-time statistical computation

5. Processing modes — supports both batch and streaming data processing for near real-time synchronization.

6. No-code API generation — instantly create RESTful APIs without microservices coding.

7. Multi-API integration — combine outputs from multiple third-party APIs in a single workflow.

8. Automated data format conversion — convert JSON, XML, CSV, and other formats without custom scripts.

9. Built-in debugging console — instant result checks and error tracking to speed up development.

10.Centralized monitoring & alerting — end-to-end oversight of integration pipelines, infrastructure, and app performance.

11. Lightweight, high-throughput — typical unit requires 2 vCPU + 4GB RAM, capable of processing millions of records in minutes.

12. Enterprise-grade resilience — scalable, secure, and compliant with regulatory and operational requirements.

The technology provider is seeking partners with multinational corporations, enterprises, and system integrators to transform integration from a technical bottleneck into a strategic enabler, delivering scalable, secure, and compliant solutions that accelerate digital transformation and data-driven decision-making.

1. Banking & Financial Services

• Modernises legacy core banking systems by integrating mainframe and cloud data.
• Automates ETL workflows for compliance, reporting, and AI-driven fraud detection.
• Reduces operational costs and shortens reporting cycles.

2. Healthcare

• Unifies patient, lab, and imaging data from multiple systems for holistic care.
• Enables real-time alerts and analytics for faster clinical decisions.
• Supports paperless workflows for patient onboarding and records management.

3. Telecommunications

• Connects customer, billing, and network data from disparate platforms.
• Enables real-time service monitoring and customer experience optimisation.
• Reduces integration time for mergers, acquisitions, or system upgrades.

4. Manufacturing

• Integrates shop-floor IoT, supply chain, and ERP systems.
• Enables predictive maintenance, quality control analytics, and production optimisation.

5. Government & Public Sector

• Consolidates siloed departmental databases for unified citizen services.
• Automates reporting for compliance, ESG initiatives, and budget monitoring.

6. Cross-Industry Applications

• Real-time data synchronisation between legacy and modern systems.
• Low-code API generation to quickly integrate new applications.
• Hybrid cloud deployment for flexible, secure data operations.

7. Agritech / Smart Farming

• Automates data collection from IoT sensors (soil moisture, weather, crop health).
• Processes and integrates sensor, drone, and satellite data in real time.
• Enables precision agriculture—optimised irrigation, fertiliser use, and pest control.
• Supports predictive analytics for yield forecasting and early issue detection.

• Rising Digital Transformation Demand – Enterprises urgently need agile, low-code data platforms to modernize infrastructure and accelerate innovation.
• Hybrid Cloud & Legacy Integration Gap – Strong demand for solutions bridging mainframes, cloud, APIs, and IoT in a seamless, cost-effective way.
• AI & Analytics Growth – Timely, integrated data is now a critical enabler for AI adoption and real-time decision-making across industries.
• Talent Shortage in Legacy Systems – Scarcity of mainframe/ETL specialists drives adoption of low-code tools that reduce technical dependency.
• Cost & Efficiency Pressures – Enterprises seek platforms that cut IT spend while delivering faster deployment and operational savings.

A versatile solution that powers AI, advanced analytics, and digital transformation across diverse sectors, including finance, healthcare, telecom, manufacturing, agritech, and beyond with many UVPs; here are the top five:

1. Significant Cost Savings – Reduces total cost of ownership by up to 90% compared to traditional ETL/data tools.
2. Unified Data Access – Connects legacy mainframes, modern databases, cloud apps, APIs, and IoT into one seamless platform.
3. Low-Code Speed – Drag-and-drop workflows cut development effort by up to 80% and deliver deployment in days.
4. High Performance, Low Resource – Processes millions of records in minutes with minimal hardware (2 vCPU, 4GB RAM per unit).
5. Near Real-Time Insights – Enables faster, data-driven decisions with clean, integrated data for AI and analytics.