Progress Data Platform FAQs
1. Platform Overview
What Is the Progress Data Platform?
The Progress® Data Platform is an AI data platform that helps organizations unify, govern and activate their data for trusted AI and analytics. It provides a semantic and governed data foundation that enables accurate, explainable AI without forcing organizations to replace their existing systems.
Who Is the Progress Data Platform Designed for?
The platform is designed for organizations that operate with complex, distributed or regulated data and need AI they can trust. It supports technical teams building AI solutions, as well as business leaders responsible for outcomes, risk and compliance.
How Is the Progress Data Platform Different from Traditional Data Platforms?
Traditional platforms focus on storing or processing data. The platform focuses on making data understandable and usable for AI by adding semantic context, governance and control, bridging the gap between raw data and reliable AI outcomes.
2. AI, RAG & Agentic AI
How Does the Progress Data Platform Enable Enterprise AI?
The platform enables enterprise AI by securely connecting to existing data sources, enriching them with semantic meaning and enforcing governance. This allows AI systems to retrieve and reason over accurate, trusted information, improving reliability, explainability and alignment with business reality.
What Is Retrieval-Augmented Generation (RAG)?
RAG is an approach that grounds AI responses in authoritative data sources instead of relying solely on a model’s training. The Progress Data Platform uses semantic RAG to generate AI outputs from your enterprise data, significantly reducing hallucinations and improving accuracy.
How Does the Progress Data Platform Reduce AI Hallucinations?
The platform uses semantic retrieval-augmented generation (RAG) to facilitate the generation of AI responses from authoritative enterprise data sources only. By unifying data, applying semantic context and enforcing access controls, the platform limits AI outputs to what is known, vetted and permitted, dramatically reducing hallucinations and unverifiable responses.
What Is the Progress Agentic RAG Solution, and How Does It Relate to the Progress Data Platform?
The Progress® Agentic RAG solution is designed for teams seeking faster time to value with agent-based AI experiences. It provides a streamlined way to deploy AI assistants and workflows, while the Progress Data Platform offers deeper control, governance and scalability for enterprise-wide AI. Many organizations use both: the Agentic RAG solution for quick wins and the Progress Data Platform for long-term AI strategy.
Does the Progress Data Platform Support Agentic and Multi-Step AI Workflows?
Yes. The platform provides a governed data layer that AI agents can safely interact with, enabling multi-step reasoning, research and decision workflows while maintaining transparency, security and control.
3. Architecture & Integration
How Does the Progress Data Platform Fit into an Existing Architecture?
The platform integrates with existing data lakes, warehouses, content systems and applications. It works alongside your current tech stack, adding semantic context and governance rather than replacing existing platforms.
What Types of Data Does the Progress Data Platform Support?
The platform supports both structured and unstructured data, including documents, databases, metadata and domain-specific content. The additional ability to ingest and search vector, graph, geospatial and temporal data allows it to operate across the full spectrum of enterprise information, not just curated datasets.
Does the Progress Data Platform Require Data to Be Moved or Duplicated?
Not necessarily. The platform can work with data where it lives, depending on architecture and use case, indexing the data at source. This reduces operational overhead while maintaining governance and performance.
4. Security, Governance & Trust
How Does the Progress Data Platform Handle Security?
The platform enforces fine-grained authentication and authorization across data and AI workflows. AI outputs respect existing permissions, allowing users to only see information they are entitled to access.
What Governance Capabilities Are Included?
The platform provides semantic governance, lineage, auditing and policy enforcement. This allows organizations to understand where data comes from, how it is used and how AI outputs are generated, supporting compliance and accountability.
Who Owns the Data and AI Outputs?
You do. Enterprise data remains under your control and is not used to train external models. AI outputs are derived from your governed data sources, preserving intellectual property and ownership.
Is the Progress Data Platform Suitable for Regulated Industries?
Yes. The platform is designed for regulated and high-trust environments, including financial services, healthcare, government and other sectors, where accuracy, transparency and compliance are non-negotiable.
5. Enterprise Scale & Performance
Can the Progress Data Platform Scale for Enterprise Workloads?
Yes. The platform is built to scale across large data volumes, distributed environments and growing numbers of users and AI workloads, without sacrificing governance or reliability.
Is the Progress Data Platform Suitable for Real-Time or Operational AI Use Cases?
The platform supports a range of use cases, from near-real-time knowledge discovery to deep analytical research. Performance characteristics can be tuned based on data, architecture and use case requirements.
How Does the Progress Data Platform Avoid Becoming a Bottleneck?
By integrating with existing systems and applying governance and semantics intelligently, the platform enables AI access without introducing unnecessary latency or complexity. Combined with the platform’s ability to ingest data as is, vectorize data specific only to the use case, dynamically build out semantic graphs and use any AI model, the Progress Data Platform grows with you and rises to your use case needs.
6. Getting Started & Adoption
How Long Does It Take to Get Started with the Progress Data Platform?
Most organizations see value within weeks. The platform supports incremental adoption, allowing teams to start with targeted use cases and expand as confidence and maturity grow.
Do I Need a Mature AI Strategy to Begin?
No. The Progress Data Platform supports organizations at all stages of AI maturity, from exploration to enterprise-scale deployment. It provides a foundation that evolves as AI capabilities and requirements expand.
What Are Common First Use Cases?
Common starting points include knowledge discovery, enterprise search, deep research, decision support and AI assistants grounded in trusted data.
How Do Teams Typically Adopt the Progress Data Platform?
Successful adoption starts with a focused use case, clear ownership and measurable outcomes. The platform integrates into existing workflows, minimizing disruption while enabling new AI capabilities.
7. Value, ROI & Long-Term Fit
How Do Organizations Measure ROI with the Progress Data Platform?
Organizations measure ROI through faster access to information, reduced manual effort, improved decision quality and lower risk from inaccurate AI outputs. The platform also helps avoid costly re-architectures and compliance issues.
How Does the Progress Data Platform Reduce AI Risk and Cost?
By grounding AI in trusted data and enforcing governance, the platform reduces the risk of hallucinations, regulatory issues and reputational damage. It also minimizes wasted effort on failed AI pilots by enabling scalable, production-ready AI from the start.
How Does the Progress Data Platform Future-Ready AI Investments?
The platform is model-agnostic and architecture-flexible, allowing organizations to adopt new AI models and technologies without the need to rework their data foundation. This produces long-term value as the AI landscape evolves.
Still Have Questions?
Talk with a Progress expert to explore how trusted data can power
AI outcomes in your organization.