h2OGPT vs. Haystack by deepset
A side-by-side comparison based on G2 review data.
| Metric | h2OGPT | Haystack by deepset |
|---|---|---|
| Overall rating | 3.9 | 4.4 |
| Review count | 13 | 11 |
| Ease of use | 8.6 | 8.4 |
| Ease of setup | 8.6 | 0.0 |
| Quality of support | 7.8 | 8.4 |
| Meets requirements | 7.9 | 8.8 |
| NPS | 15.384615 | 63.636364 |
| Small Business | 76.9% | 50.0% |
| Mid-Market | 15.4% | 30.0% |
| Enterprise | 7.7% | 20.0% |
| Total page views | 42 | 66 |
| Total LLM citations | 47 | 766 |
h2OGPT
h2oGPT is an open-source platform developed by H2O.ai, designed to provide a private and efficient environment for deploying and interacting with large language models (LLMs). It enables users to run GPT models locally, ensuring data privacy and control without reliance on external servers. The platform supports various data types, including documents, images, and videos, facilitating versatile applications across different domains.
- Ease of Use
- Text Generation
- Versatility
- Natural Language Processing
- Accuracy
- Open Source
Haystack by deepset
Haystack is deepset's open-source Python AI orchestration framework for building customizable, production-grade AI agents and workflows. Connect components like language models, vector databases, and file converters into pipelines and agents that retrieve, reason, and act on your own data; use hooks to control the agent loop: enforce a token budget before the next LLM call, incorporate human approval before a risky tool call, or use compaction to keep context small.
- Natural Language Processing
- Ease of Use
- User Interface
- Open-Source
- Scalability
- Time-saving