Path to AI

The Path to Adopt AI

Engage in a 360 degree infrastructure and information security assessment to prepare deliver your data to AI

First Step

Ask yourself what data or what process do you want to deploy in AI?
Consider isolate important data or as a backup in a private cloud infastructure
Deploy pentests and vulnerability analysis into your information sources
Engage in purple team activities to assess you potential security threats
An lastly, leave a 360 degree solution running monitoring all your potential threats

Is your data ready for AI?, most likely it is not! Vectorization of your structure and unstructure information is now needed

Second Step

For a more successful implementation of AI, more particularly in LLM App development, vectorization of your data is needed
Vectorization means applying vectors, which are mathematical matrices, to locate and compare better your information
Vectorization is needed more for unstructure data but improves the overall performance if all data, including structure data is vectorized"
Unstructure data includes resources such as: pdfs, images, photographs, videos, audio transcripts"
We are agonostic to Vector Databases, although we have worked with Pinecone, Mongo Atlas or Chroma "

Get advantage of the LLM rationalization capability and build innovative applications for your organization

Third Step

LLM stands as Large Language Model, introduced by Open AI as Chat GPT in November 2022
LLM Apps covered RAG (Retreival Augmented Generation) implementations, read your docs
Read your databases with Natural Language
Utilze seamlessly functionality such as text to speech, speech to text or speech to speech
Build applications in areas such as, customer service, sales, operations and finance