How reliably can inconsistent product records be reconciled? Can source-grounded retrieval improve a defined sourcing task? How can an agent stay within approved tools and permissions as enterprise context changes? Each question needs a baseline, test dataset and reproducible evaluation.
Innovation & intellectual property
Define the problem. Document the contribution.
Our development direction connects industry-specific information, enterprise context and controlled AI workflows. Technical novelty and ownership are established through project evidence and agreements.
Questions worth testing
Modules and technical records
Potential reusable components include data connectors, ontology definitions, retrieval pipelines, approval workflows and evaluation tools. Project records should identify the source revision, architecture, dependencies, data permissions and test results. This page does not claim a patent, registered IP portfolio or independently proven technical breakthrough.
Ownership and collaboration
Written agreements must distinguish pre-existing IP, newly developed software, customer data, third-party licences and permitted reuse. Do not infer ownership from a team member’s previous employment or a platform demonstration. The applicable contract determines each party’s rights.
From research to a reviewable milestone
Discovery establishes the research question and data access; a controlled prototype tests feasibility; deployment adds integration and acceptance; expansion tests repeatability. Budget categories can include engineering, data preparation, evaluation, integration, security and training. Any funding application requires its own eligible scope, cost evidence and current programme assessment.