PrivateGPT vs Progress Agentic RAG
PrivateGPT
privategpt.dev
Progress Agentic RAG
progress.comSide by side
| Figure | PrivateGPT | Progress Agentic RAG |
|---|---|---|
| Price from | Free | $700/mo |
| Free plan | Yes | — |
| Free trial | — | Yes |
| Open source | — | — |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | — |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 3 |
| Spec score · Retrieval-Augmented Generation Tools | 8.6 (#4) | 7.9 (#14) |
| Deployment | PrivateGPT can be installed as a Python package, from source, or with Docker, and runs as a local server. | Deployment options include Progress-managed cloud in Europe or the USA and hybrid processing in the cloud with storage in the customer's local NucliaDB instance. |
| Integrations | Documented integration guides cover Claude Code, Claude Desktop, Claude for Microsoft 365, and OpenCode. | Retrieval agents can query knowledge boxes, SQL databases, internet search services, and MCP servers in one response. |
| Purpose | PrivateGPT provides an open-source API layer for building private AI applications on your own infrastructure. | Progress Agentic RAG provides a centralized agentic knowledge layer connecting enterprise content to AI experiences. |
| Support | The maker links to a community Discord for users. | Starter includes community support, Pro includes community support plus ZenDesk, and Enterprise includes a private Slack channel plus Zendesk. |
Plans
Progress Agentic RAG
- Starter$700 a month
- Pro$1,925 a month
- EnterprisePriced on request
In their own words
PrivateGPT
PrivateGPT is a free, open-source API layer for building private AI applications on your own infrastructure. It does not run models itself: it connects to a separate OpenAI-compatible inference server, which can be local or remote. The Messages API supports streaming, asynchronous processing, and token counting. Document workflows include file and artifact ingestion, retrieval with citations, and tools for querying databases and analyzing tabular data. The documented capabilities also include web search and extraction, code execution, custom tools, and MCP connectors. A browser workbench at `/ui` can be used for demos and inspecting API requests, but it stores chats and settings in browser localStorage and has no access control; the documentation describes it as a local demonstrator. PrivateGPT can be installed as a Python package, from source, or with Docker, and runs as a local server. Package installation requires Python 3.11; Python 3.10 and 3.12 or later are unsupported. Platforms include Linux, macOS, Windows, web, API, and self-hosted environments.
Progress Agentic RAG
Progress Agentic RAG has no write-up on Specifiction yet; its figures are above.