AI Beyond R&D: BlueCat’s Vision for the Future of Software

BlueCat Networks invites you to an onsite event on June 26, where we will explore how AI is transforming the software industry from the ground up. Learn how we ethically empower non-R&D teams such as Marketing and Product Management to use tools like ChatGPT, while addressing legal and compliance challenges.
Our team of experts will share BlueCat’s journey, from internal adoption to the development of AI-powered solutions in Network Operations. The event will include a live demo, practical insights, and a look at how we are staying ahead in a rapidly evolving AI landscape.
This event is free and open. If you want to join, please register on the following link: https://www.linkedin.com/events/aibeyondr-d-bluecat-svisionfort7339320885868130305/
Agenda:
18:30 - 18:45: How BlueCat overcame obstacles for adopting AI? - Paul Gray, SVP Engineering.
18:45 - 19:00: Guiding Principles for Building AI into our product – Stephen Pendleton, Senior Principal Software Developer
19:00 - 20:00: How LiveAssist evolved to keep pace with AI advancements? – Vuk Radovanovic, AI Software Developer
20:00 - 21:00: Networking
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How BlueCat Overcame Corporate Obstacles for Adopting AI (15 Minutes)
Speaker: Paul Gray, SVP Engineering
Companies enabling employees to ethically use AI tools face multiple practical, ethical, and compliance-related challenges. At BlueCat we established an AI committee to address the following topics:
Data Privacy and Confidentiality to ensure employees don’t disclose sensitive company or customer information.
Accuracy and quality of data results to ensure employees don’t rely too heavily on generated data w/o verification as AI generated data contains bias from their training data.
Compliance and legal risks ensuring AI usage complies with industry-specific regulations (e.g., GDPR, HIPAA, …) including intellectual property and copyright ownership of AI-generated content.
Learn how BlueCat overcame internal reluctance to move quickly into the new AI first world by (1) proving the value of AI for all teams, (2) establishing clear guidelines on acceptable AI use scenarios (3) establishing scalable governance mechanisms to monitor and audit AI usage, and (4) selecting proper AI tools.

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Guiding Principles for Building AI into our Software Product (15 Minutes)
Speaker: Stephen Pendleton, Senior Principal Engineer
Fifteen months ago, we knew it was time to augment our product with AI. We had pressure from our customers, competition, and investors. We were very encouraged because our competition focused on the less impactful uses of AI by focusing on RAG solutions around setting up or using their product.
We wanted to do something evolutionary and leapfrog our competitors because we collect, correlate, and store more data than our competition for longer periods of time. We have a massive data warehouse of Packets, Flow, SNMP, and API data. We want to utilize AI with our unmatched data to help our customers proactively solve their Network problems.
We were VC funded at the time and did not have a bench of resources to throw at building a solution, so we came up with three guiding principles: (1) write as little code as possible and (2) don’t train models, and (3) abstract away from any single LLM provider. These principles saved us money and enabled us to move quickly at AI-velocity reflected in the open-source coding community and LLM providers. We are building on the efforts of millions of brilliant developers and data scientists.

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How LiveAssist Evolved to Keep Pace with AI Advancements (60 Minutes)
Speaker: Vuk Radovanovic ML/AI Engineer
Learn how LiveAssist evolved from the initial reactive monolithic Chatbot application to a proactive self-learning multi agent system proactively solving real customer issues using internal data sources to a current goal aware MCP enabled solution using internal and external data sources to solve more real-world customer issues faster.