LIVE! Nov 13 South Bay Unstructured Data Meetup

5:30 - 6:00 - Welcome/Networking/Registration
6:05 - 6:30 - Dinesh Chandrasekhar, Challenges in Structured Document Data Extraction at Scale with LLMs
6:35 - 7:00 - James Luan, Milvus 2.4
7:05 - 7:30 - Rob Quiros, Beyond RAG Partitions: Per-User, Per-Chunk Access Policy
7:30 - 8:00 - Networking
​​Tech Talk 1: Challenges in Structured Document Data Extraction at Scale with LLMs
Speaker: Dinesh Chandrasekhar, Unstract
Abstract: All businesses have to deal with unstructured documents at some level. Some have to deal with them at scale. While an LLM-powered approach to this problem is most certainly head and shoulders above traditional machine learning-based approaches, it is not without its challenges. Top concerns being accuracy and cost, which can really begin to hurt at scale.
In this talk, we will look at how Unstract, an open source platform purpose-built for structured document data extraction, solves these challenges. Dealing with 5M+ pages of structured content extraction per month, Unstract uses various techniques to attain accuracy and cost efficiency.
Topics Covered
Introduction to Unstructured Data Processing
Processing Document Data
Extraction Difficulties
Unstract to the rescue
Demo
​Tech Talk 2: Milvus 2.4
Speaker: James Luan, VP of Engineering, Zilliz
​Tech Talk 3: Beyond RAG Partitions: Per-User, Per-Chunk Access Policy
Speaker: Rob Quiros, CEO & Co-Founder, Caber Systems, Inc.
Abstract: Partitioning vector databases has proven to be a useful tool for privacy and per-tenant isolation. Recent releases of vector db software, including Milvus, have continued to improve partitioning capabilities such as pushing the number of partitions into the millions and providing improved selection of partitions per tenant.
​Despite these advances, management overhead increases with the number of partitions. Relative to the capabilities enterprises require and have come to expect from their existing storage systems and databases, there is still a shortfall. New capabilities specific to how vector databases store data and how they are used in RAG applications are needed.
​Topics Covered:
​- Origins of enterprise requirements for granular access control and policy in storage systems.
Sensitive data identification: data classification versus access control.
The problem data-duplication in enterprise datasets presents when copying permissions from documents to chunks.
How enterprise access requirements can be met with per-user, per-chunk access control
Case study and example implementation.