AI-enabled Professional Standards Assessment and Training Needs Analysis (Individuals and Organisations)

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Note, this is a contract award notice and not a call for competition. The Education and Training Foundation (ETF) intend to award a contract for the provision of an AI Professional Growth Coach Platform. ETF is the professional body for the further education sector, supporting practitioners and providers with continuing professional development, quality improvement and sector development. ETF has multiple assessment tools in use and sought a supplier to consolidate them under a new Digital and AI Framework with clear outputs and CPD pathways. ETF has an agreed technology direction: the desired skill scan solution needed to be a web-accessed application surfaced via ETF's Umbraco website, leveraging Azure B2C Single Sign-On already in place; core business data resides in Microsoft Dynamics 365 CRM. Scope of work: The Education and Training Foundation (ETF) has procured a supplier, following its internal competitive Request for Quotation process, to design, develop and implement a new digital assessment and CPD‑support platform for the Further Education sector. The scope of the contract includes: 1. Professional Standards Assessment Development of a digital self‑assessment tool aligned to the ETF Professional Standards for Teachers, Trainers and Leaders. The solution will capture confidence and frequency scores, reflective comments, and generate both quantitative and qualitative insights. Organisational-level benchmarking and automated links to CPD recommendations are required. 2. Training Needs Analysis (TNA) Creation of integrated Individual (ITNA) and Organisational (OTNA) Training Needs Analysis functionality. The platform must identify priority training gaps, produce visual outputs (including web/spider diagrams), support strategic workforce planning, and enable evaluation across impact, engagement, and workplace transfer of learning. 3. CPD and PDP Integration A fully connected workflow between assessment outputs, CPD resources and Personal Development Plans (PDPs). Individuals must be able to set priorities, track progress, record reflections, and achieve milestones. Completed CPD should update PDPs automatically, with features to promote learner engagement and motivation. 4. AI‑Driven Recommendation Services Implementation of explainable AI to map assessment results to relevant CPD opportunities from ETF’s offer, its LMS, and appropriate external content. The service must support personalisation based on learner preferences such as time availability and learning style, while including mechanisms to detect and minimise bias. 5. Reporting and Evaluation Delivery of dashboards for individual, organisational, and sector‑level reporting. Outputs must cover training priorities, confidence–frequency diagrams, evaluation metrics, and benchmarking (subject to consent). Data exports to CSV/Excel and integration with Power BI are required. 6. Non‑Functional Requirements The supplier must meet ETF and DfE standards for: - Security and Compliance: GDPR/UK DPA, encryption, role‑based access, audit trails, data‑retention controls, and provision of materials for the DfE Authority to Operate process (e.g., security plan, DPIA inputs, penetration test results). - Accessibility: Compliance with WCAG 2.2 AA. - Performance and Availability: <2‑second response times at P95 and defined SLAs and error budgets. - Interoperability: Open APIs and webhooks for CRM, LMS, and Umbraco CMS integration. - Ethical AI: Measures to monitor, mitigate, and correct algorithmic bias. 7. Systems Integrations The service will integrate with: - ETF’s Umbraco website via Azure B2C SSO - Dynamics 365 CRM for profiles, organisations and consent - The ETF Learning Platform (Thought Industries) and curated CPD resources - Power BI for analytics 8. Deliverables The contract covers: - Discovery, architecture, UX and security model design - MVP build: assessment tools, TNA, PDP, AI recommendations, dashboards - Integrations with Umbraco, Dynamics 365 and LMS - Assurance pack and security artefacts - Pilot and user testing (including accessibility verification) - Handover, documentation, runbooks, and training Process: In September 2025 ETF conducted proportionate pre-market engagement, supported by an independent technology and AI consultant, to identify suppliers with demonstrable capability in AI-enabled assessment platforms. Using objective criteria (experience in AI projects, platform maturity, and integration capability), ETF shortlisted three suppliers invited to submit expressions of interest. ETF confirms no conflict of interest existed in the consultant’s involvement, and all suppliers were treated equally and without discrimination. The short-listed suppliers, were asked to submit an expression of interest containing the following content: 1. Executive Summary. 2. Technology & Architecture (hosting, security, AI design, integrations). 3. Functional Fit (Professional Standards, TNA, PDP/CPD integration, outputs). 4. Delivery Plan & Risk Management. 5. Costs & Commercials (one-off, annual, assumptions). 6. Case Studies (2 or more relevant solutions). 7. Assurance & Compliance (CE+, ISO 27001, AtO experience). 8. Accessibility & UX approach. 9. Support Model (SLAs, onboarding, knowledge transfer, exit plan). The following evaluation criteria and weightings were provided to all shortlisted suppliers within the RFQ documentation and were applied consistently and objectively: - Functional fit – 30% - Architecture, security & integrations – 20% - UX & accessibility – 10% - Delivery approach – 15% - Cost of ownership – 15% - Case studies & team – 10% A contract was awarded to the highest scoring supplier and unsuccessful suppliers notified. The contract term included the delivery period plus associated warranty / support obligations to ensure full life-cycle coverage, resulting in an end date of 28 August 2026. The total contract value (including all options, extensions, and warranty): £213,000 including VAT.

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