Skip to main content

(PMIA) SOPHiA

Sophia Prototype is here

While the MVP version of Sophia is under development, we have prepared a preview version of the core with non-autonomous abilities (AI workflow planning and execution) in a sandbox. You can test the staged operation in a non-autonomous model, and try your ideas about a self-learning AI with expandable memory, and workflow planning methodology.

How PMIA Works?

PMIA is a complex solution containing:

  • A pretrained AI, acting as a machine brain
  • A fully trainable AI model, acting as a machine memory with virtually unlimited context space
  • A flexible Graph database, able to remember everything in a fully flexible way
  • A traditional database, able to provide the PMIA with unlimited storage and retrieval capability
  • A highly sophisticated workflow design and expediting process controller that helps PMIA do its job unsupervised.
PMIA At Core

At PMIA Core, two AI models are in constant debate. One learns and remembers every detail you provide, and then reviews the information, plans workflows, executes them, and ensures the workflow is successfully concluded.

Starting from the first hello, and keep going until the last goodbye, the PMIA remembers everything, not just in a recorded shape: it tries to understand them, resolve the conflicts, extract the most important parts and best of all: keeps doing the hard job for you.

How PMIA works with my data

SOPHiA is composed of five key parts: a Thinker AI, which acts as the brain cell, a Memorizer RAG which learns every input you give them, two databases which structurally manage your data (SQL / Graph) and a Core Orchestrator. All parts are weaved with highest reliability and security standards. So its learning abilities also remain inside the PMIA workflow.

SOPHiA classifies what it receives from you into five main categories:

Organizational data, Project Structure, Project running data/reports, Standards and Knowledge.

While every new practice is immediately effective, later you can easily transfer the best practices and project lessons learned to the next project, without any concern about mix-up, conflicts or information leakage.