# What NLP platforms are actually worth using for teams that need strong user adoption and minimal training requirements, rather than a platform that only data scientists can operate?

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Hi all, I'm comparing what NLP platforms are actually worth using for teams that need strong user adoption and minimal training requirements, rather than a platform that only data scientists can operate. Plenty of NLP tools assume a specialist at the keyboard, so the useful question is which ones a broader team can actually run. Here's what comes up across the <a class="a a--md" elv="true" href="https://www.g2.com/categories/natural-language-processing-nlp-platforms">Natural Language Processing (NLP) Platforms category</a>.</p><ul>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/datasaur/reviews"><strong>Datasaur</strong></a><strong>:</strong> Reviewers specifically note that non-technical users can use it without intense training, so annotation work isn't gated behind data scientists. Collaboration and quality-control features keep a mixed team consistent.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/ibm-watsonx-orchestrate/reviews"><strong>IBM watsonx Orchestrate</strong></a><strong>:</strong> The plain-language interface and pre-built agents let business users trigger and complete tasks without code, which is the point for teams that don't want a specialist-only tool. Advanced flows still benefit from technical help.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/ibm-watson-natural-language-understanding/reviews"><strong>IBM Watson Natural Language Understanding</strong></a><strong>:</strong> Reviewers describe it as easy to use and understand, with little machine-learning background needed for the core API, so a broader team can work with results, though some JSON familiarity helps.</li>
</ul><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">For broad adoption, what lets non-specialists actually use the platform, a no-code interface, plain-language interaction, or simple output to work with? And where did you still end up needing a data scientist despite the promise of ease?</p>

##### Post Metadata
- Posted at: 5 days ago
- Author title: Marketing
- Net upvotes: 1


## Comments
### Comment 1

&lt;p&gt;Datasaur seems best for broad, non-technical adoption because the interface and review workflows let people contribute without understanding the underlying models. Watsonx Orchestrate also lowers the barrier through plain-language actions, but more complex automations are where technical support usually becomes necessary.&lt;/p&gt;

##### Comment Metadata
- Posted at: 5 days ago
- Author title: Marketer





## Related discussions
- [How well does Trello scale into a larger team?](https://www.g2.com/discussions/1-how-well-does-trello-scale-into-a-larger-team)
  - Posted at: about 13 years ago
  - Comments: 6
- [Can we please add a new section](https://www.g2.com/discussions/2-can-we-please-add-a-new-section)
  - Posted at: about 13 years ago
  - Comments: 0
- [Quantifiable benefits from implementing your CRM](https://www.g2.com/discussions/quantifiable-benefits-from-implementing-your-crm)
  - Posted at: about 13 years ago
  - Comments: 4