AI isn't a buzzword at PAGS. It's a toolkit built around the work that actually eats SENCO and teacher time. Upload a statutory support-plan document — an EHCP in the UK — and turn it into an action plan. Generate a term's progress summary in minutes. Match tomorrow's lesson to the right learner targets. Reword targets to fit the child's age, at one click.
Every PAGS AI feature is initiated by a user, reviewed by a user, and approved by a user. The AI never writes anything to a learner record on its own. Nothing is hidden. Nothing is automated. You decide when to use it, what to feed it, and what to keep. More on how we keep AI safe →
Six places PAGS AI lifts the workload. Every one designed around a real school task that used to take hours.
Upload an EHCP or similar support-plan document. AI extracts objectives, targets, strengths, needs, parent voice, and learner voice. SENCO reviews and saves each item.
Generate a summary of progress notes against targets, objectives, or any custom date range. Save a template and run it again next term.
Tell PAGS the lesson. AI picks the learner’s most-relevant active targets and returns age-appropriate tasks, strategies, and evidence prompts.
Group selected targets into a broader objective, or break an EHCP outcome — or IEP/ISP goal — down into the smaller step targets that build the pathway. Both directions.
PAGS highlights any target reading younger than the learner’s chronological age and rewrites it in personalised, age-appropriate language at a click.
AI reads existing assessments, progress notes, learner details, and voices, and drafts a compelling supporting letter. SENCO reviews and edits.
Print the document. Block out the rest of the week. Read every page, take notes, re-key the objectives and targets into the system, copy the strengths and needs into the profile, log the parent and learner voice somewhere safe. The action plan starts to take shape next Monday at the earliest.
Upload the EHCP PDF. Microsoft Presidio strips the identifiers. PAGS AI returns the objectives, targets, strengths, needs, parent voice, and learner voice, one card per item. Review, edit, accept. By the end of the meeting, the learner record carries every fact in the document, and you can start linking targets to objectives and building the plan.
The result: hours of typing become minutes of reviewing. The clinical detail in the EHCP shapes the support plan from day one, not day eight.
Open each learner record. Read every progress note from the last twelve weeks. Try to remember what fit which target. Write a paragraph each for cognition, communication, self-regulation, academic progress. Multiply by thirty learners. Lose the weekend.
Pick a learner. Choose the developmental area, an objective, or a custom date range. PAGS AI summarises the progress notes already recorded against the relevant targets, returning a draft summary that captures what happened, what worked, and where to focus next. Save it. Save the template. Run the same report next term in seconds.
The result: end-of-term reports are written in an afternoon, not over the weekend, and the language stays consistent because it draws from the actual progress notes staff have been recording all term.
Pull up the lesson plan. Check the SEND register. Open each learner profile, find their active targets, mentally pair them to the lesson content. Decide what to differentiate. Hope you remembered everyone.
Paste the lesson into PAGS AI. The AI scans each learner’s active developmental, academic, and custom targets, picks the ones that fit the lesson, and returns age-appropriate tasks, strategies, and evidence prompts for each. The teacher walks in with a sheet that already says “these seven targets, these seven tasks, in this lesson, with these evidence collection cues.”
The result: SEND-aware differentiation without the planning overhead. Targets stop living in a separate document. They live in the lesson itself.
Gather a year of progress notes from a shared drive. Print assessment results. Pull the parent voice from an email thread. Find a Word template, start writing the supporting statement, balance the clinical detail with a coherent case for additional support. Hope the chronology holds together.
PAGS AI reads the assessment results, progress notes, learner details, provision history, parent voice, and learner voice already in the platform, and drafts a compelling supporting letter. The SENCO reviews, edits, and signs. Every claim in the letter is backed by data already in the system, so the supporting evidence pack is a single export away.
The result: stronger applications, less staff time, and a defensible case for additional support that the Local Authority can read in a single document.
Educators stay in control. Personally identifiable information is anonymised before AI sees it. The platform runs on enterprise Azure OpenAI in the EU, and school data is never used to train public models. The full story is on the Responsible AI page.
Bring a real EHCP, IEP, or ISP, a recent batch of progress notes, or a lesson plan you’ve already written. We’ll show you how AI handles it inside PAGS, end to end, with you in the driver’s seat the whole way.
EHCP document import, progress summary generation, lesson-target matching, target creation, target rewording, objective generation and breakdown, and AI application letter generation are all live features at the time of writing. The full guided EHCP Application Flow is in active development. Last reviewed: June 2026.