Now accepting pilot applications

Legal analysis tools for
SEND professionals

AI-powered screening and validation that applies the statutory legal framework to EHCP evidence bundles and plans — in seconds, not hours.

1.3%
LA tribunal win rate 2023–24
£153m
Spent defending appeals annually
25,000+
Appeals registered 2024–25
60 sec
vs 2–3 hours manual review

Two tools. Two critical points in the EHCP process.

Both tools apply the current statutory legal framework — Children and Families Act 2014, SEND Code of Practice 2015, and SEN Regulations 2014.

1

Evidence Bundle Screener

Upload an EHCP evidence bundle and receive a structured legal analysis in about 60 seconds. Applies the two-limb statutory test, maps evidence against CoP 2015 para 9.14 criteria, and flags every missing document under SEN Regulations 2014.

Legal framework: s.36(8) Children and Families Act 2014 · CoP 2015 para 9.14 · SEN Regs 2014 Reg 6(1)

Eligibility verdict:

YES PROBABLY YES UNABLE TO DETERMINE PROBABLY NO NO
2

EHCP Quality Validator

Upload a completed or draft EHCP and validate every section against the statutory requirements. Flags vague and unenforceable language, checks every Section B need is matched to a specific Section F provision, and identifies tribunal risk before a plan is issued.

Legal framework: SEN Regs 2014 Reg 12(1) · s.37(2) CFA 2014 · CoP 2015 para 9.61 · Case law: B-M v Oxfordshire (2018) · JD v South Tyneside (2016)

Plan quality verdict:

COMPLIANT REQUIRES AMENDMENT NON-COMPLIANT

Upload. Analyse. Download.

1

Upload

PDF, DOCX, scanned documents, handwritten letters — all supported via AWS Textract OCR.

2

Analyse

Claude AI reads every document and applies the statutory legal framework — in about 60 seconds.

3

Review

Structured analysis with verdict, evidence citations, missing document flags and tribunal risk.

4

Download

Professional PDF report suitable for panel use, annual reviews and tribunal bundles.

No system integration required. Works standalone alongside any case management system including Liquidlogic, Mosaic and Eclipse.

Built for the hardest period SEND teams have ever faced.

Reduce tribunal exposure

Every eligibility decision includes a tribunal risk assessment and draft decision letter text — so refusals are legally defensible before they leave the panel.

Free up caseworker capacity

Reduces manual bundle review from 2–3 hours to under 20 minutes — giving teams capacity back during the SEND reform transition period.

Legally documented decisions

Every finding is cited directly from the submitted documents. A clear audit trail for every eligibility and quality decision — exactly what tribunals expect.

Ready for reform

The current legal framework remains in force until at least 2028–29. The tool applies existing law today and is built to adapt as the new framework is legislated.

No IT integration needed

Completely standalone. Upload documents, download a PDF report. Works alongside any existing case management system without any technical deployment.

UK data only

All processing on AWS eu-west-2 (London). Nothing ever leaves the UK. Document data is never used to train AI models. Full Data Processing Agreement provided.

Grounded in current statutory law.

Every finding is mapped to specific legislation, statutory guidance or case law. Not opinion — a structured legal analysis.

Request a free pilot

A small number of pilot places are available for local authorities and SEND professionals. No cost, no commitment, no IT integration required.

Or email directly: [email protected]  ·  Goggle Software Ltd

Important: EHCP Toolkit is an AI-assisted legal pre-screening tool. All output must be reviewed by a qualified professional before any decision is made. It does not constitute legal advice and is not a substitute for professional judgement. Legal framework applied: Children and Families Act 2014 · SEND Code of Practice 2015 · Special Educational Needs and Disability Regulations 2014. Data processed exclusively on AWS eu-west-2 (London). Nothing leaves the UK. Documents are not used to train AI models.