Lamini Agentic Use Cases

Lamini is a platform that allows you to fine-tune LLM models with your own data. It provides a space where you can interact and see different outcomes from Q&A on various fine-tuned training sessions. Their premise is:

AI automation is only useful when it’s accurate. Our platform enables you to reduce hallucinations while keeping inference latency and cost low.

They are currently focusing on agentic use cases, and here is an outline of some of them:

Clasification (CAT)

This is basically the process of categorizing text into predefined categories based on its content.

• See the documentation in:

https://docs.lamini.ai/cat/

• Some code:

[embed]lamini - Lamini Docs Edit descriptiondocs.lamini.ai

Use cases:

A grocery delivery service company tags products based on various attributes — category, dietary preference, sale items — to make it easier for customers to find the items they need.

An e-commerce retailer classifies product reviews by sentiment to understand how products are performing.

A customer support organization classifies incoming support tickets to route them to the right departments.

An airline classifies user feedback into 600 classes to identify changes to their service and understand user trends.

A financial services company stratifies user complaints into different degrees of urgency that follow compliance and regulatory turnaround.

Text2sql

Text-to-SQL is a natural language processing (NLP) task that turns plain text into SQL queries

• See the code:

https://github.com/lamini-ai/llama-recipes/tree/main/recipes/3p_integrations/lamini/text2sql_memory_tuning

You can read more here:

[embed]Text-to-SQL: Achieving 95% accuracy | Lamini - Enterprise LLM Platform Text-to-SQL is a natural language processing (NLP) task that turns plain text into SQL queries. The goal is to empower…www.lamini.ai

Some advantages here is that you can reach 95% of accuracy using this approach!

Function calling

Function calling refers to the capability of a model to interact with external tools or APIs to perform specific tasks.

• See the API, it garantees valid Json output:

[embed]REST API Edit descriptiondocs.lamini.ai

You can read more here:

[embed]Build High-precision Function Calling Agents | Lamini - Enterprise LLM Platform Function calling refers to the capability of a model to interact with external tools or APIs to perform specific tasks…www.lamini.ai

[embed]Guarantee Valid JSON Output with Lamini | Lamini - Enterprise LLM Platform TL;DR: Structured outputs are required for production-ready LLMs. In the past, engineers had to write custom parsers…www.lamini.ai

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