Sherpa AI Server#

Sherpa AI Server is a web service application designed for training, using, and fine-tuning large language models (LLM) within the closed perimeter of corporations. Sherpa AI Server combines a document vector storage, offline model management, support for various artificial intelligence models – with different sizes, with quantization and without, their deployment on GPU or CPU, designing data processing chains, API access, a robotics platform, a web interface, and much more.

Sherpa AI Server is an Artificial Intelligence Center that contains functionality for:

· large language models (LLM) in a closed perimeter;

· web chat for company employees in the style of ChatGPT with history and dialogues;

· support for the Russian language;

· answers to questions based on proprietary documents;

· built-in document vector storage;

· API for any company applications, compatible with OpenAI;

· integration with Sherpa RPA - working with LLM from robot scripts;

· security, confidentiality, monitoring, auditing;

· multi-user and multi-threaded mode;

· choice from over 300 available language models;

· operation with CPU / GPU and the latest methods of quantization and batching of neural networks;

· the possibility of integration with any domestic RPA platform via API.

Sherpa AI Server has a wide range of capabilities and functionalities that can be applied as:

· a chatbot for customer support;

· a chatbot for internal user support;

· a chatbot for answering questions about corporate documents and knowledge bases;

· a document builder, contract generator, job postings, reports, analytical notes;

· a legal robot, sales robot, HR robot, interview robot, document management robot, etc.;

· extraction of structured and unstructured data from documents, including scanned ones, and entering them into information systems;

· generation of content plans, blog posts, articles, reviews, comments, press releases, digests, email letters, newsletters, presentations, etc.;

· generation of code, unit tests, macros, queries, comments, and documentation for code;

· semantic analysis and sentiment analysis of comments and customer feedback;

· text and voice BI (Business Intelligence) for corporate data;

· mass copying of document edits, tracking, and supporting changes in regulatory documentation.