"If you're loading your million documents into a review platform, as an example, and then immediately culling out 800,000 of them for not hitting keywords or not being part of TAR or whatever, you still have these 800,000 documents sitting there in your database that you're paying for and that are exposed from a risk factor after leaving your corporate environment,"
"This means only relevant documents - already tagged with first-pass decisions on issues like privilege, confidentiality and responsiveness - are loaded into expensive hosting platforms. How MARC Works MARC operates as a text analytics tool that sits between data collection and the review platform. The system is agnostic about which large language model (LLM) it uses. Organizations can deploy MARC with Altorney's provided Llama model installed locally, or integrate it with their preferred approved models, including those from Azure or OpenAI."
Altorney released MARC for general availability to corporate legal teams, litigation service providers and law firms after a pilot with corporate legal departments. The product automates first-pass review decisions to prevent entire document sets from being loaded into expensive hosting platforms, reducing costs and minimizing security exposure from non-responsive documents. MARC sits between data collection and review platforms as a text analytics tool that tags documents for privilege, confidentiality and responsiveness before hosting. The system is agnostic about underlying LLMs and can run locally or integrate with approved models such as Azure or OpenAI.
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