AI Application Assessment

Manual grant application processing creates significant administrative backlogs, placing undue burden on assessment teams and delaying critical funding distribution.

Our AI Application Assessment engine streamlines your funding pipeline by extracting key evidence from applicant submissions, evaluating claims against your published criteria, and generating clear, auditable scoring summaries. Built entirely within Microsoft’s secure enterprise ecosystem, the system acts as an intelligent assistant for your Programme Heads and Trustees while ensuring human reviewers retain complete control over every funding decision.

Core Capabilities of the Assessment Engine

1. Automated Evidence Extraction & Structuring

Grant applications often include lengthy project proposals, financial breakdowns, and supporting governance documents. Our assessment engine scans submitted documentation to isolate key facts, metrics, and eligibility claims automatically.

  • Extracts unstructured narrative text, financial spreadsheets, and PDF evidence into structured Dataverse records.
  • Identifies missing documentation or incomplete eligibility criteria prior to full panel review.
  • Highlights key project outcomes and financial figures for rapid reviewer inspection.

2. Criteria & Rubric Matching

Evaluating applications consistently against complex scoring guidelines can be challenging across multiple assessors. The assessment engine systematically compares applicant evidence directly against your specific grant criteria.

  • Evaluates submitted evidence against qualitative and quantitative scoring rubrics.
  • Provides citation-backed evidence snippets showing exactly where an applicant met or missed a criterion.
  • Maintains strict impartiality by evaluating all submissions against identical baseline rules.

3. Auditable Scoring Summaries

Transparency and governance are paramount in grant distribution. The assessment engine produces comprehensive review digests that document the exact rationale behind every extracted score.

  • Generates standardised summaries tailored for Programme Heads, advisory panels, and Trustees.
  • Provides complete audit trails detailing how raw applicant text was mapped to specific evaluation criteria.
  • Exports structured scoring data directly into Power BI dashboards for portfolio-level analysis.

4. Human-in-the-Loop Governance

Our system is designed to augment human judgment, not replace it. AI performs the labor-intensive evidence extraction and criteria matching, leaving final evaluation and award decisions entirely to your decision-makers.

  • Assessors can override, adjust, or comment on any AI-suggested score.JPG
  • Human reviewers retain 100% authority over final funding decisions.JPG
  • Fully compliant with UK Data Protection, GDPR, and public sector governance standards.

Enterprise Security & Architecture

Built natively on Microsoft 365, Copilot Studio, Power Apps, and Dataverse, the AI Application Assessment engine integrates directly into your current workspace.

  • Tenant Boundary Protection: All applicant data remains safely within your agreed Microsoft security boundary.
  • Zero Model Training: Your proprietary scoring rubrics, guidance documents, and applicant submissions are never used to train external public AI models.
  • Purview Compliance: Fully compatible with Microsoft Purview, Data Loss Prevention (DLP), and Conditional Access security policies.

Flexible Technical Deployment

Choose from Client-Hosted, Managed Service, or Hybrid deployment options to match your internal IT capability. Review our Flexible Deployment Options to evaluate technical architectures.

Experience the Assessment Engine in Action

Before making changes to live operational systems, you can evaluate how our AI application assessment workflow processes applicant data. We provide interactive demonstrations using a fully fictional Microsoft 365 demonstration environment.

Test criteria matching, review generated scoring summaries, and explore the reviewer interface without exposing real grant-maker or applicant data.