TECHNOLOGY / IN DEPTH

AI, Machine Learning & Generative AI

We identify the technical contribution in AI and machine learning systems by examining the path from input to output. Improvements in training, inference and implementation are assessed against earlier approaches and the technical effects they produce.

WHAT WE REVIEW

Key technical and IP issues

  1. 01

    Review data selection, cleaning and augmentation together with model architecture, loss functions and training order.

  2. 02

    For LLMs and RAG, examine retrieval, ranking, context construction, tool calls and response validation.

  3. 03

    Document implementation-linked effects such as latency, memory consumption and error reduction, as well as accuracy.

Information to support the initial review

  • Model and data-flow diagrams
  • Comparison of baseline and improved approaches
  • Experimental setup, metrics and results

You can begin a discussion before all the documents are available. Your development stage and planned disclosures help us establish priorities and agree the scope of work.

Turning technical analysis into an IP plan

Our technical analysis guides prior art searches, filing strategy, prosecution and rights analysis. We agree the scope, deliverables and timetable for each engagement.

Put your IP strategy into practice.