Unstructured Platform logo

    Unstructured Platform

    Unstructured extracts and transforms data for use with every major vector database and LLM framework

    Ratings and reviews

    5
    1 ratings
    4 star
    3 star
    2 star
    1 star
    100%
    0%
    0%
    0%
    0%
    1 AWS reviews

    Filters

    Review type

    AWS Marketplace reviews
    External reviews
    Reviews (1)
    reviewer2846073

    Fast document parsing has boosted culture insights and now improves HR policy intelligence

    Reviewed on Jun 04, 2026
    Review from a verified AWS customer

    What is our primary use case?

    We are a culture operating system that analyzes organizational culture, and we have an AI bot that joins calls to create structured culture intelligence reports. When we talk about HR, there are HR policies, PDFs, and performance documents generated by the HR or human resource department in the company. If we need to digest that data, we use Unstructured to create a vector database of these unstructured data.

    If an HR manager wants to use HR policies, HR documents, and performance data in Instill, they can upload their document, and we use Unstructured to convert those PDFs into a vector-based database.

    What is most valuable?

    We are now using Unstructured every day, and it is useful when we want answers and AI to be used on a PDF or something similar. We use Unstructured to convert it into a vector database to make retrieval augmentation or any kind of AI processes easy.

    The document parsing stands out, as the document ingestion is very fast in Unstructured, 20 to 40% faster than the industry products available. If HR wants to upload a PDF on our platform, we use Unstructured to digest the data, and it is 20 to 40% faster than other solutions.

    The faster document ingestion has resulted in customer satisfaction, leading to higher quality answers using AI that improved customer satisfaction and NPS score. NPS has improved by at least 10 to 15 points since we started using Unstructured, not only for data digestion but also for retrieving data when we have to use AI or RAG.

    What needs improvement?

    Cost is something that needs to be factored for scaling use cases because we do not have control over how many documents users will upload, so it is variable and we cannot set a threshold.

    For how long have I used the solution?

    I have been working in my field for the last eight years.

    What do I think about the stability of the solution?

    The accuracy and reliability of output from Unstructured are very accurate and highly reliable, as we have not faced any issues and the uptime is consistent.

    Which other solutions did I evaluate?

    I advise doing research about other vector database searches because Pinecone is also good, but you need to understand the use case.

    What other advice do I have?

    Features and usability are fine, and it is one of the best products available.

    I chose a rating of 10 out of 10 because they are very focused on doing what they do at the best quality and speed, and what they are not doing is outside their scope. They claim faster processing and converting into a vector database faster, building a vector database from unstructured data, which they provide at a very fast speed and quality.

    The governance and security regarding Unstructured's AI capabilities are good, as we have SOC 2 and other compliance certificates from Unstructured. I give this product a rating of 10 out of 10.

    Which deployment model are you using for this solution?

    Private Cloud

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?