News
Key Takeaways
- Progress Software Launch. New Agentic RAG SaaS platform helps enterprises adopt generative AI with more accuracy and scalability.
- Affordable Enterprise AI Adoption: Progress Agentic RAG is available on AWS Marketplace and Progress.com, starting at $700 per month.
- Built for the Enterprise. The platform supports multilingual data ingestion, intelligent search and integration with multiple enterprise LLMs.
Progress Software has officially rolled out Progress Agentic RAG, a SaaS-based retrieval-augmented generation (RAG) platform designed to make generative AI more trustworthy, accessible and verifiable for organizations of all sizes.
The Big Picture: Why This Matters
Generative AI adoption is booming, but one issue continues to dominate the conversation: trust. Companies love the idea of AI-powered insights, but concerns around accuracy, security, bias and governance have slowed full-scale adoption.
According to company officials, Progress Agentic RAG aims to help businesses extract verified answers from unstructured data — whether that’s text, audio, video — while keeping costs and complexity in check.
Who Benefits from Progress Agentic RAG?
Built with flexibility in mind, this platform is designed to serve:
- IT leaders and development teams at mid-to-large enterprises
- Small businesses and departmental teams needing affordable AI tools
- Organizations managing massive volumes of unstructured data across different formats and languages
In other words, Progress is endeavoring to tackle pain points for Fortune 500 IT leaders all the way to small departmental teams.
Related Article: C3 AI Launches No-Code Agentic Process Automation for Enterprises
The State of AI Adoption in 2025
“Agentic AI is reshaping how organizations interact with data and drive decision-making. Cost-effective solutions like Progress Agentic RAG that are built for easier deployment can help businesses unlock productivity and innovation and be at the forefront of this transformation — regardless of their size."
- Amy Machado
Senior Research Manager, IDC
While generative AI may be everywhere in the headlines, in practice, it’s still early days.
- 88% of organizations are actively monitoring GenAI’s evolution.
- Yet only 10% of deployments have moved beyond experiments into real production use.
- Security, privacy and reliability remain the biggest obstacles.
Many organizations are experimenting with AI for search, summarization, content generation and knowledge management, but IT departments are under pressure to implement governance frameworks to ensure accuracy and compliance.
Progress, with its new RAG platform, is attempting to bridge the gap between experimentation and enterprise-grade AI adoption.
Why RAG Technology Matters
At its core, retrieval-augmented generation (RAG) blends the static training data of large language models (LLMs) with real-time search capabilities. Responses aren’t just generated from memory. Instead, they’re backed by up-to-date, verifiable sources.
This hybrid approach reduces hallucinations and builds user trust — exactly the challenges enterprises face today.
Following its acquisition of Nuclia, Progress uses the company’s database (NucliaDB) to serve as a foundation for scalable, semantic and multilingual search.
"Progress Agentic RAG, which we started using as Nuclia, has fundamentally changed how we access and act on information across our organization. Its ability to deliver fast, accurate and verifiable insights from our unstructured data has been a game-changer for productivity and decision-making."
- Patrick Garcia
Chief Digital, AI & Innovation Officer, SRS Distribution
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Inside the Platform: Capabilities That Stand Out
| Capability | Description |
| No-Code RAG Pipeline | Ingests multilingual text, audio and video with AI agents. |
| Intelligent Search | Delivers fast, multilingual answers from unstructured data. |
| AI Agent Deployment | Provides retrieval functionalities directly to AI agents. |
| Multi-Model Integration | Lets enterprises choose and control their preferred LLMs. |
| Purpose-Built Database | Leverages NucliaDB for semantic, keyword and metadata search. |
| RAG Evaluation Metrics | Built-in tools ensure traceability and answer quality. |
The Takeaway for Enterprises
Progress is joining a growing movement to make AI more reliable and enterprise-ready. By addressing core concerns like data accuracy, compliance, privacy and accessibility, Agentic RAG positions itself as a key player for organizations moving beyond AI experimentation into production-scale adoption.
For enterprises still hesitant about how to operationalize AI responsibly, Progress’ new platform could mark a turning point in building long-term trust in generative AI.
