Practical Artificial Intelligence. Real Business Impact.

Broadpin enables and extends the built-in AI capabilities of Oracle Fusion Cloud Applications. Our teams help customers adopt new AI functionality across ERP, HCM, SCM, CX, EPM, PPM, and OPC. Both during implementations and for existing environments.

Typical use cases include intelligent invoice matching, AI-assisted HR content creation, AI-powered user assistance, and continuous process optimization as Oracle releases new features. Oracle Fusion also provides a growing number of out-of-the-box AI agents through AI Agent Studio. We help organizations evaluate which of these agents support their specific business needs, identify the most impactful use cases, and develop tailored solutions where the standard offering needs to go further, such as AI-powered routing of HR helpdesk requests or forecasting agents that incorporate external data into production planning.

Every use case is evaluated from a process perspective to ensure real operational benefit.

Broadpin designs generative AI solutions and intelligent assistants that automate and augment business processes beyond Oracle Cloud Applications across JD Edwards, E-Business Suite, Primavera, and hybrid environments that may include non-Oracle systems.

These solutions range from intelligent assistants that support order creation and purchase order monitoring directly within JD Edwards, to multi-agent architectures for complex master data management, to AI-driven document processing that extracts structured data from shipping notices or validates contract documents for billing workflows. We also build assistants that interact with ERP systems through natural language and voice commands, enabling users to work with enterprise data in entirely new ways.

Where it fits the environment, we work with OCI Generative AI services, Microsoft Copilot Studio, and open-source tooling to deliver the right architecture for each use case. The technology choice always follows the process need, not the other way around.

AI changes how users interact with data. Broadpin leverages AI capabilities in Oracle databases, analytics platforms and the new AI Data Platform to enable natural-language access to structured and unstructured data, build predictive models, and create intelligent data platforms that go far beyond basic querying.

A growing number of our projects use Oracle Database 23ai and 26ai to vectorize enterprise content (documents, regulations, manuals, claims records) and make it searchable through semantic search. This allows users to query information by meaning rather than exact keywords, producing faster, more relevant results. We implement these capabilities across diverse contexts: enabling semantic search over internal procedures and regulations, building AI-powered search across claims and policy documentation, or connecting natural language queries directly to E-Business Suite or Fusion data through Select AI.

Beyond search and retrieval, we help organizations build AI-ready data platforms that support predictive analytics, demand forecasting, anomaly detection, and data-driven decision-making at scale. We also enable AI Assistants within Oracle Analytics Cloud, allowing business users to query semantic models in natural language turning complex analytical questions into immediate, accessible insights.

With OCI AI Data Platform, we extend these capabilities into a unified, governed data foundation that integrates data ingestion, transformation, storage, analytics, and AI services. This enables organizations to combine data from across the enterprise, apply vector search and machine learning at scale, and operationalize AI securely and efficiently. The platform ensures data consistency, governance, and performance while accelerating the development of AI-driven use cases.

The goal is not more dashboards, but faster insight, better predictions, and smarter decisions for business users.

Not all AI is customer-facing. Broadpin also uses AI internally to support assessments, modernization efforts, and the implementation of projects. These capabilities are applied during project execution and are not embedded into customer operations afterward.

Our Horus BPM platform uses the Model Context Protocol (MCP) together with large language models to automatically generate business process models from unstructured input, dramatically increasing the speed and consistency of process documentation. For implementation projects, we use AI to semi-automatically generate requirement documents, technical concepts, and project documentation based on proven templates and methodologies. We also leverage AI for code generation. For example, producing APEX customizations faster and with higher consistency than manual development. Additionally, our PITSS.CON tools use AI to further automate Forms-to-APEX migration, both for standalone Oracle Forms applications and for custom forms within Oracle E-Business Suite environments.

Additional internal use cases include AI-assisted validation of customer documentation for cloud assessments, automated TCO calculations and business case derivation, and a mandatory AI training program for our consultants and developers ensuring that AI capabilities are embedded into our delivery culture, not just our tooling.

• Intelligent invoice processing and exception handling

• Natural language queries on E-Business Suite and Fusion financial data

• AI-powered order management and purchase order monitoring

• Contract document screening for milestone-based billing

• Automated shipping notice processing and data extraction

• AI-generated job descriptions and profiles

• Resume analysis and content assistance

• Intelligent routing of HR helpdesk requests through AI agents

• Support for performance reviews and HR processes

• AI-supported exception handling and quality monitoring

• Forecasting agents incorporating external data such as weather conditions into production predictions

• Predictive demand planning and inventory optimization

• Automated document processing for logistics workflows

• AI agents for PDF extraction and field population in Fusion

• Natural language queries on enterprise data via Select AI and Oracle 23ai/26ai

• Semantic document and data search using vector embeddings

• Predictive analytics, anomaly detection, and intelligent forecasting

• AI Assistants in Oracle Analytics Cloud for conversational BI

• Knowledge base construction with AI-powered retrieval

• AI-ready data platforms for enterprise-scale intelligence

• AI-powered legacy code analysis and automatic documentation using PITSS.CON

• AI-accelerated Forms-to-APEX modernization with PITSS.CON

• AI-assisted code generation for APEX customizations

• Automated business process modeling from unstructured input

• Semi-automated generation of requirement documents and technical concepts

• AI-assisted cloud assessments and TCO calculations

• AI-assisted schedule risk analysis with early identification of delays and bottlenecks

• Predictive forecasting of project timelines, costs, and resource utilization

• Intelligent progress tracking through automated data capture from field updates and reports

• Natural language querying of project schedules, tasks, and portfolio data

• AI-driven issue and risk classification with recommended mitigation actions

• Automated document analysis for contracts, RFIs, submittals, and change orders

• Resource optimization using predictive insights across projects and portfolios

• Anomaly detection in project performance, highlighting variances in cost, schedule, or productivity

• Integration of external data (weather, supply constraints, labor availability) into project forecasts

• AI copilots to assist project managers with reporting, decision support, and stakeholder communication