Your admissions handbook, running as a live engine. The language model reads. Your rules decide. Your team validates, capable of processing 100 applications every minute.
AutoEnrol captures your admissions rules, including the ones that only live in evaluators' heads, and runs them as a live engine your team validates. Institution-specific, auditable, and consistent by design.
Most admissions rules live in individual evaluators' heads. We work with your team to surface them, including thresholds, prerequisites, country equivalencies, and exceptions, and put them somewhere the whole institution can see. Often the first time your rule set has existed as a single artifact.
Transcripts, certificates, and test scores read by a language model trained on global credentials. Every field extracted, every value evaluated against your rules. Same input, same output. Low-confidence cases route to your team for validation.
Accept, Conditional, Missing Information, Reject, or Refer. Every recommended decision ships with an easy to understand rationale and a decision tree linking the applied course rules back to the source documents. Your team reviews, validates, and owns the final call.
Transcripts, certificates, test reports, and passports. Scanned, photographed, low-resolution, or multi-page. Native coverage of 100+ countries and credential systems, with bounding-box traceability back to the source page. This is where AI is, and only where AI is. Your rules still decide.
Measured across transcripts, degree certificates, English test reports, and government-issued IDs, including photographed pages, skewed scans, and non-Latin scripts.
Compressed time-to-decision. Policy-aligned outcomes. Full decision lineage. Evaluators focused on the cases that need extra institutional judgement and correspondence with the applicant.
Compressed from the 45-minute manual baseline to machine speed. Every file, every time.
To process 100 applications end-to-end. Documents in, recommendations out.
Across transcripts, certificates, test scores, and supporting documents, including photographed pages and non-Latin scripts.
Rules-based evaluation produces identical outcomes on identical inputs. Same file, same answer, every time.
Students multi-apply and compare time-to-decision. Institutions that decide in days capture the applicants institutions that decide in weeks have already paid to generate.
Your criteria applied identically to every application, every time. Fairness becomes repeatable execution, not aspiration.
Every recommendation traceable to a specific rule and a specific document. Easy to understand rationale, generated alongside the recommendation, not reconstructed afterwards.
Evaluators validate every recommendation rather than rubber-stamp it. AutoEnrol sits under the team, not above it, so the institution stays visibly in control of who gets in. Throughput lifts without the burnout, allowing evaluators to focus on cases that need more of their institutional judgement.
Every institution that has tried to build its own admissions rule engine has discovered the same thing: the rule surface is deeper than it looks. One large provider reached roughly 8,500 rules before the project was paused. AutoEnrol is what you switch to when your in-house team hits the asymptote.
GPA thresholds, English requirements, subject prerequisites. The rules you can hand to an intern.
Qualification mappings, program-by-program overrides, regional institution tiers. The rules your senior evaluators carry in their heads.
Conditional pathways, exception patterns, edge credentials, fraud signals. The rules nobody has written down, including the ones you don’t know you apply.
AutoEnrol doesn't ask any stakeholder to compromise their core responsibility. Each persona gets what they need, without trading off the others.
Faster credible offers protect yield. In a market where students multi-apply and compare time-to-decision, slow evaluation quietly leaks class quality you've already paid to generate.
Absorb peak-cycle surges without adding headcount or compromising review quality. Evaluators can shift focus away from repetitive checks and onto the decisions that need detailed judgement.
AutoEnrol handles the rule-bound baseline and flags the cases that need your expertise. You validate recommendations, not rubber-stamp them. The platform sits under the team, not above it.
ISO 27001. Regional data residency. API-ready for SIS and CRM integration. Pilots run with zero production touch. And your engineers don't spend the next two years building a rule engine that never finishes.
See AutoEnrol's recommendations next to your team's manual outcomes, rule-by-rule, with zero integration and zero policy compromise. Your team validates; the pilot shows you where the engine agrees and where it doesn't.
Across three courses you choose. Real historical applications, fully de-identified.
No API hookups, no SIS changes. Data flows via a secure transfer, and nothing touches production.
Every AutoEnrol recommendation benchmarked against your manual outcome, rule-by-rule.
University-grade data handling, from day one of a pilot through full production deployment.
Certified information security management. Independently audited controls over data handling and confidentiality.
Processing and storage in-region by default. AU, EU, UK, US options available.
Pilot data flows in fully anonymised. Nothing identifying ever leaves your institution.
Every recommendation carries a complete rule-by-rule audit trail you can replay at any time.
Built for the concerns procurement, IT, and faculty raise before anyone signs anything.
By 2030, admissions decision infrastructure will be table stakes. The institutions that get there first win the next decade of international talent.
Book an intro call →