We incorporated state-of-the-art LLMs into Conveyor in 2022 and we haven’t stopped pioneering a better (easier) way to let AI take on the manual tasks of security reviews.
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Let’s set up your POC today, so you can see for yourself.
ConveyorAI leverages best in class LLMs for different tasks, and uses a multi-hop approach to get the most accurate information for different question types.
Easily link ConveyorAI to any source for use in answer generation like external websites, help centers, product releases, documents, product marketing decks, company wikis, Q&A pairs, and past answers.
Every answer is validated to ensure consistency with the data sources, and includes the cited sources as reference, drastically reducing the chance for hallucinations.
Every answer is sourced, cited, and securely linked so you know where the answer came from.
Conveyor uses custom Retrieval Augmented Generation (RAG) techniques to convert your internal and external context into a single source of information. The LLM can then use that index to source and cite generated answers with a bias for recency.
The Conveyor engine translates complex queries, routes them logically to specialized LLMs, and constructs queries into a vector database. Complex indexing and retrieval flows constantly autosync new information - the system is always learning and improving.
The Conveyor engine understands the intent, verbosity, and natural language when answering security questionnaires or RFPs. There are no “black boxes”: every generation includes source citation and link. Workflow tools always export to the original format in a single click.
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