SF Bay ACM Chapter

Deploying and Scaling Large Language Models in the Enterprise: Architecting Multi-Agent AI Systems Integrating Vision, Data, and Responsible AI

LOCATION ADDRESS (update - virtual)

If you want to join remotely, you can submit questions via Zoom Q&A. The zoom link:
https://acm-org.zoom.us/
Join via YouTube:
https://youtube.com/live/

AGENDA
7:00 SFBayACM upcoming events, introduce the speaker
7:15 speaker presentation starts
8:15 - 8:30 finish, depending on Q&A

Join SF Bay ACM Chapter for an insightful discussion on:

Abstract:
Large Language Models (LLMs) are rapidly reshaping enterprise AI, but real-world deployments demand far more than fine-tuning and API calls. They require sophisticated architectures capable of scaling inference, integrating multi-modal data streams, and enforcing responsible AI practices—all under the constraints of enterprise SLAs and cost considerations.
In this session, I’ll deliver a deep technical dive into architecting multi-agent AI systems that combine LLMs with computer vision and structured data pipelines. We’ll explore:

• Multi-Agent System Design: Architectural patterns for decomposing enterprise workflows into specialized LLM-driven agents, including communication protocols, context sharing, and state management.
• Vision-Language Integration: Engineering methods to fuse embeddings from computer vision models with LLM token streams for tasks such as visual question answering, document understanding, and real-time decision support.
• Optimization for GPU Inference: Detailed strategies for memory optimization, quantization, mixed-precision computation, and batching to achieve high throughput and low latency in LLM deployment on modern GPU hardware (e.g., NVIDIA A100/H100).
• Observability and Responsible AI: Techniques for building observability layers into LLM pipelines—capturing token-level traces, detecting drift, logging model confidence—and implementing fairness audits and risk mitigation protocols at runtime.

Drawing on practical examples from large-scale enterprise deployments across retail, healthcare, and finance, I’ll discuss the engineering trade-offs, tooling stacks, and lessons learned in translating research-grade LLMs into production-grade systems.
This talk is designed for AI engineers and researchers eager to understand the technical complexities—and solutions—behind scaling multi-modal, responsible AI systems that deliver real business value.

Speaker Bio:
Dhanashree is a Senior Machine Learning Engineer and AI Researcher with over a decade of experience designing and deploying advanced AI systems at scale. Her expertise spans architecting multi-agent solutions that integrate Large Language Models (LLMs), computer vision pipelines, and structured data to solve complex enterprise challenges across industries including retail, healthcare, and finance.
At Albertsons, Deloitte, and Fractal, Dhanashree has led the development of production-grade AI applications, focusing on optimization, model observability, and responsible AI practices. Her work includes designing scalable inference architectures for LLMs on modern GPU infrastructures, building hybrid pipelines that fuse vision and language models, and engineering systems that balance performance with ethical and regulatory considerations.

She actively collaborates with research institutions like the University of Illinois. Dhanashree actively engages with the research community and frequently speaks on bridging advanced AI research and production systems.

https://www.linkedin.com/in/dhanashreelele/

The Association of Computing Machinery http://www.acm.org/about-acm/about-the-acm-organization is the world’s largest computing society, handling Computer Science conferences and publications. The San Francisco Bay Area ACM is a local professional chapter, a non-profit 501c(3), founded in 1957. We hold two public presentations a month on (1) General Computing is on the third Wednesday of the month, and (2) Data Science SIG, on data mining, deep learning or big data on the 4th Mondays, and (3) Life science on the third Wednesday of a month. Among these Meetups, we recently emphasis Security & Social Modeling discussions, and AI in life science.

We are introducing more talks on Genetics and Medicine normally 30-80 people attending our talks since returning in-person meetings after the pandemic years.

See also our YouTube channel (https://www.youtube.com/user/sfbayacm) with OVER 240 past talks. And you can find our Security & Social Modeling talks on YouTube playlist: https://www.youtube.com/playlist?list=PL87GtQd0bfJyVsBgkL-TyNzZhsNOYK2v_ .

SEEKING SPEAKERS
In general, we are seeking speakers to book in advance. Talks could be like something you would see at a computing conference, an educational subject for experienced computing professionals. It is fine to err on the side of more technical, algorithmic or mathematical.
If you would like to submit a talk proposal, please provide the following:

• 2 available dates (General Computing and Life Science on 3rd Wednesdays) or (DS on 4th Mondays). We skip December for talks.
• speaker name, phone, email, LinkedIn (or picture)
• talk title
• talk description (include any desired links, related reading)
• speaker bio (include any desired links)

CALL FOR PRESENTATIONS IN general computing area as listed by ACM:
* internet of things
* cyber security
* information retrieval
* semantic web
* virtualization
* embedded and real time systems
* cryptography
* bitcoin & related block chain
* human computer interaction
* virtual reality
* large scale networks
* robotics
* quantum computing
* 5g or 6g wireless

And hot topics in Silicon Valley:
* startups, VC funding, how to pitch to VCs
* women or minorities in computing (to support)
* hiring or being hired
* science fair
* computing to support fusion, lab works for national projects
* major open source software
* Genetics
* Bio Info
* Medicines

Coordinating with professors from Stanford, we6 will introduce more speakers in Genetics, Bio Info and Medicine regularly on the 1st Tuesday. Available dates for Data Science: 12/2/2025, 1/26/2026
General computing: 9/17, 11/19/2025, 1/21/2026

We are open to accept proposals for 2026, please specify which months you will be available on either the 3rd Wednesday or the fourth Monday in 2026 with your abstract proposal.

CONTACT US
On the left side of the Meetup page, in the "Organizers:" box, there is a "Contact" button you can use for the submission, use "general computing", "LifeS", "S&S" or "DS SIG" talk at the beginning to propose your talk. You may send your proposal to Speakers@sfbayACM.net for multiple attentions as well.

SPONSORSHIP OPPORTUNITIES
You can also contact me (Greg Makowski) about sponsorship opportunities for our non-profit organization. We are run by unpaid volunteers. If you provide financial sponsorship, sponsor food or the video recording for a night or talk series, we can offer either
a) a "thank you for the donation letter with our 501c(3) non-profit tax ID" for your tax deduction
b) "thank the sponsor" time to address the event audience during the "upcoming events" period of one of our events (7:00 - 7:10)
c) opt-in registration information of the attendees
d) "thank the sponsor" branding on the video, posted on our YouTube video channel of our talks
e) a banner in our monthly email newsletter to 5,000 opt-in bay area computing professionals or a section of our print newsletter to members only
f) make a suggestion and we can see what we can do, constrained by our volunteer effort and non-profit status.

Thanks,
Liana Ye, Program Chair, and Greg Makowski, Business Development Lead and Data Science SIG Chair