A Practical Guide to Reducing Latency and Costs in Agentic AI Applications
Scaling companies that are actively integrating Large Language Models (LLMs) into their agentic AI products are likely to face two significant challenges—increasing latency and costs: increasing traffic and long prompts lead to slower response times (latency) from LLMs, this can negatively impact user experience and sales, and application costs increase exponentially as API (Application Programming…
Why Georgian Invested in Coder
We are excited to announce that Georgian has led Coder’s $35M fundraise…
Why Georgian is Investing in SurrealDB
The proliferation of unstructured data has, in our view, made building modern…
Redefining Legal Impact with the Team at Darrow
When we think about legal tech software, we think about value add…
Testing LLMs for Trust and Safety
We all get a few chuckles when autocorrect gets something wrong, but…
Introducing Georgian’s “Crawl, Walk, Run” Framework for Adopting Generative AI
Since its founding in 2008, Georgian has conducted diligence on hundreds of…