Aineko

Optimizing LLM performance can be hard given how quickly the landscape is moving. Everyday, new AI papers are released proposing new methods that offer a potential performance gain. Struggling to figure out where everything fits? Read my latest post where I give a high-level overview on how the industry is thinking about improving LLM performance!

⚙️ Optimizing LLM Performance: Key tactics for Evaluation and Enhancement In the latest post of our blog series on developing high-quality production intelligent applications, we detail key strategies for measuring and improving the performance of LLM apps. We explore methods including prompt engineering, retrieval-augmented generation (RAG), and fine-tuning, assessing their effectiveness, impact, and limitations. https://lnkd.in/gxXC_fTi 💭 We'd love to hear from you! Tell us about the methods you've used, what succeeded, and what fell short. ✨ Follow us for more! #AIagents #ProductionAgents #AI #ArtificialIntelligence #promptengineering #RAG #finetuning

I've built a lot of intelligent agents during my career in capital markets. I saw first-hand how they transformed that industry. I'm excited for what's to come in other industries. Developments in generative AI are unlocking tons of new cases. Read my latest post on the Aineko blog to learn what AI agents are all about.

🚀 Beyond LLMs: Demystifying AI Agents In the kickoff to our blog series on building production-grade intelligent agents, we explore the journey of AI agents from simple bots to sophisticated systems capable of transforming industries. We delve into how these agents are redefining the landscape across various sectors, the critical components that make up an intelligent agent, essential considerations in their development, and key insights for deploying production-ready agents. https://lnkd.in/edHJ6zwT 💭 We welcome your thoughts! How do you envision AI agents impacting your industry? ✨ Follow us for more! #AIagents #ProductionAgents #AI #ArtificialIntelligence 

This week our CEO, Ricardo Rosales, presented at the Data Engineer's Lunch hosted by Anant Corporation. Tune in to learn how you can use Aineko to build event-driven AI applications, including RAG pipelines with high quality outputs.

We've heard developers want to leverage LLMs, but are having a hard time getting to production. In prod you have to account for biz logic, compliance, and QA. Here's an example demonstrating an LLM feature with real-time QA built on Aineko https://hubs.la/Q0253zjh0

Check out this case study on building a code generation LLM feature with real-time QA using Aineko. One developer built it in less than a week and we want to help you do the same.  Aineko makes it possible to rapidly prototype, automate deployments, and unify observability for real-time user experiences. If you’re thinking about any of the following for your product, we’d love to chat: 1) Real-time AI inference, generative AI workflows or live QA for AI apps 2) Interactive, multi-user, or real-time user experiences for your product 3) Getting to market fast without the headaches of managing infrastructure We’re looking for a few more teams to join our closed beta. Get started with Aineko Open Source with zero fees & zero commitment. Book a demo: https://lnkd.in/gKkdMZec

The last couple of months, the Aineko team and I have been heads down building. This post details why I think what we're working on is so special. Would love to chat if you're interested in trying out Aineko or if you'd like to help us continue build it.