Continuous, audit-ready evidence. Every framework, one source of truth.
Accreditation & Evidence is the operating layer under your reviews: evidence is captured where the work happens and tagged to the criterion it proves, KPI values are computed deterministically and bound to the documents behind them, and coverage is live every day. The submission for CAA, MQA, NAAC, NBA, ABET, AACSB, TEQSA, NCAAA or your US regional is derived, not rebuilt.
The problem
Evidence is collected after the fact. It should be captured as work happens.
Every QA director knows the email that goes out a month before the visiting team arrives: send me the assessment samples, the marking schemes, the minutes, anything showing we closed the loop. What follows is a search party, not quality assurance. The marking scheme exists somewhere, the minutes were taken by someone who has left, and the number in the self-study is right while the document that proves it is three laptops away.
Collecting means going to find evidence later. Capturing means it lands in the right place, tied to what it proves, at the moment the work happens. The first is a project you survive; the second is a property of how the institution operates.
The operating model
One evidence base. Every submission derived from it.
Four design choices turn accreditation from a project into a state: evidence enters at source, classification is assisted but human-confirmed, numbers travel with their proof, and every framework is a derived view of the same truth.
Capture at the source
Evidence enters where the work is done: a faculty member uploading a marking scheme inside their own course, a coordinator attaching minutes to the decision they just made. The person closest to the work is the only one who can capture it cheaply and correctly.
Tagged to the criterion as it lands
The system proposes the standard, KPI, course and term from a controlled vocabulary, and a person confirms. Assisted, not automated: a tagging policy that actually runs, instead of one that exists on paper.
The number is bound to its proof
KPI values are computed deterministically from institutional data and travel with the documents behind them. "Does the number match the document?" stops being a hope and becomes a property of the system.
Frameworks are derived views
The evidence and KPI layer is regulator-agnostic. CAA, MQA, NAAC, NBA, ABET, AACSB, TEQSA, NCAAA and the US regionals are configured as derived datasets and scorecards, so a new accreditor is configuration, not a data-entry project.
Global by design
Built for the accreditor in front of you, wherever you operate.
Most accreditation tools are shaped around one region's regulator. Here the evidence base is neutral and each framework is a mapping over it, so a university running two national reviews and three programme accreditations does the work once.
Institutional licensure and programme accreditation
Ministry-shaped datasets derived from one source of truth, with KPI scoring on published anchors and weighted pillars.
Malaysian quality and programme standards
Provisional and full accreditation, programme standards and self-review, with evidence reused across submissions.
Indian institutional and programme frameworks
Criterion-wise evidence, DVV-ready data trails and NIRF submissions computed from the same operational record.
US regional and specialised accreditation
Standards mapping, assessment cycles and closing-the-loop narratives with the evidence attached to each claim.
Quality assurance and business accreditation
Standards-based self-evaluation with continuous improvement evidence, not a document written from scratch.
Regulatory reporting and rankings
Compliance reporting, provider information requests and ranking submissions built from the same evidence and KPIs.
Inside the product
The whole accreditation cycle, in one place.
This is the application, not a diagram. Move through the surfaces your teams work in: the command centre, the evidence library and its tagging queue, standards coverage, KPI scoring, the submission pack, and corrective action plans.
| Framework | Criterion | Evidence bound | Status |
|---|---|---|---|
| CAA | 3.2 Assessment of learning | Marking schemes, samples, moderationCourses · 128 artefacts | Complete |
| MQA | COPPA 2 Curriculum design | Programme reviews, board minutesGovernance | Complete |
| NAAC | 1.3 Curriculum enrichment | Attainment reports, syllabiAssessment · OBE | Complete |
| ABET | Criterion 4 Continuous improvement | Loop-closing actions, CAP recordsAction plans | 2 gaps |
| AACSB | Standard 5 Assurance of learning | Faculty qualification, AoL cyclesFaculty · Assessment | Complete |
Lifecycle or product
The lifecycle is the operating model. This is the product that runs it.
Two pages, two jobs. Read the lifecycle to understand how quality work connects to teaching, faculty and outcomes; read this page to see the application your QA team logs into on Monday.
One of the institutional lifecycles: the governed model for how quality, evidence and accreditation run across the institution.
The application that runs it: command centre, evidence library, standards coverage, KPI scoring, submission pack and action plans.
Where does evidence come from, how does quality connect to teaching and outcomes, and what does each stage feed?
What do QA directors, coordinators, faculty and reviewers actually see and do in each screen?
The full quality operating model, including course evaluation, outcomes, rankings and institutional effectiveness.
Evidence to submission: capture, tagging, coverage, KPI scoring, packs, reviewer access, corrective actions.
You are buying or replacing accreditation software.
See inside the product →
More than a self-study tool
Why it beats an assessment-management suite.
Most accreditation software is a place to assemble a self-study before a review, with data re-keyed across modules that do not share it. This is the operating layer underneath: your data derives the submission, the numbers compute themselves, and readiness is live in the framework you actually report against.
Collected after the fact, in a pre-review project, from drives and inboxes.
Captured at source as work happens, inside the course, committee or review that produced it.
Manual tagging that never happens at scale, so a tidy library is still just files.
Assisted, human-confirmed: the system proposes standard, KPI, course and term; a person approves in seconds.
Calculated in spreadsheets, hard to trace back to the document behind them.
Computed deterministically and bound to their proof, reproducible by hand at any time.
A model shaped around one region's accreditor; a second framework means a second project.
Regulator-agnostic base: CAA, MQA, NAAC, NBA, ABET, AACSB, TEQSA, NCAAA and the US regionals as derived views.
Re-keyed into the accreditation tool, then drifting from the systems of record.
Already there: the same Academic OS runs admissions, curriculum, assessment, faculty and outcomes.
Learned when the accreditor announces it.
Scored continuously, per criterion and per programme, long before you submit.
The rules you can rely on
Assisted, not automated. Governed by design.
The product does the heavy lifting: deriving datasets, computing scores, surfacing gaps, proposing next actions. A person always owns the truth. These are the guarantees underneath every screen.
The system suggests; people decide
AI proposes tags, drafts and next actions, and a person approves. Nothing is filed, scored or submitted automatically.
Numbers cannot be faked
KPI values are computed deterministically and reproducible by hand, on demand. AI never authors a number.
The submission cannot drift
Framework datasets are derived from one source of truth and locked by default, rebuilt all-or-nothing, so they can never quietly disagree with operational data.
Freezing is a human act
Freezing results, publishing a document and submitting are deliberate human acts. A published record is immutable and dated forever.
Readiness is not a score
Readiness measures evidence completeness, never KPI performance, so one is never mistaken for the other.
Access is enforced server-side
Role, profile and scope are applied in your own database with row-level security. External reviewers get scoped, time-bound, view-only slices.
Built for every role
One product. A different day for everyone who touches it.
Owns the review: lives in the command centre, approves proposals, and freezes the results and stands behind them.
Runs the cycle and the accreditor relationship with coverage and gaps visible daily, not at the deadline.
The product scoped to one programme: its criteria, KPIs and gaps, with programme-level weights of its own.
A five-minute request answered inside their own course. No framework to learn, no folder to find.
A scoped, time-bound, view-only slice: exactly their sample, scored against the rubric, nothing more.
What quality teams say about running accreditation on Creatrix.
The Creatrix Campus application has not only helped to evaluate our curricula; it has been key in organising the documentation necessary for accreditation. The team engaged with us regularly and no query or change was a problem; they understood our vision and enhanced the software to make it happen.
A comprehensive and user-friendly platform that seamlessly integrates academic, administrative and evaluation processes in one place.
Go deeper
From the Creatrix library.
Blogs, whitepapers and case studies for the people who carry the review: QA directors, accreditation managers, IQAC and institutional effectiveness teams.
Frequently asked
Plain answers about accreditation and evidence.
Which accreditation frameworks does it support?
The evidence and KPI layer is regulator-agnostic, and each framework is configured as a derived view with its own scorecard.
Institutional and programme frameworks in use include CAA and MoHESR, NCAAA and ETEC, MQA with COPPA, COPIA and the IQAF, NAAC, NBA and NIRF, TEQSA, the US regionals such as WSCUC, MSCHE and SACSCOC, and programme bodies including ABET, AACSB, EQUIS, AMBA and ASIIN.
How is this different from an assessment-management suite?
A suite gives you somewhere to assemble a self-study before a review, with data re-keyed across modules that do not share it.
Here the submission is derived from the systems the institution already runs on, values are computed deterministically and bound to the documents that prove them, and coverage is live rather than reconstructed under pressure.
Does the AI decide our KPI scores?
No. Values are computed by a deterministic engine using the framework’s official formulas and published anchors, and every value is reproducible by hand.
AI proposes tags, drafts and next actions; a person always confirms. AI never authors a number.
Do faculty have to learn the framework?
No. A faculty member uploads a marking scheme or attaches minutes inside their own course or committee, the way they already work.
The system proposes the standard, KPI, course and term, and a reviewer confirms in seconds, so evidence arrives already classified.
Can one artefact satisfy several standards?
Yes. Evidence is tagged from a controlled vocabulary, so a single assessment sample can serve a national regulator, a programme accreditor and an internal review at once, without being copied or re-uploaded.
Can we see where we stand before a review?
Yes. Coverage is measured per criterion and per programme, and KPIs are computed continuously, so readiness is visible on an ordinary Tuesday.
Readiness measures evidence completeness and is kept separate from KPI performance, so a strong score never hides a missing artefact.
What happens to findings and gaps?
They become corrective action plans: one issue, one owner, defined actions, a target date and a status tracked to closure.
The system can pre-fill a plan from the gap it found, and a person always creates, owns and closes it.
How does submission work?
Framework datasets are derived from one source of truth and locked by default, rebuilt all-or-nothing so they cannot drift from operational data.
Freezing results and submitting are deliberate human acts, and a published document freezes into an immutable, dated record that registers itself into the evidence library.
How do external reviewers and visiting panels get access?
Through scoped, time-bound, view-only access to exactly their sample, with scoring against the rubric inside the platform.
Access is enforced server-side by role, profile and scope, so a panel never sees more than its remit.
Where does our data live and how is it secured?
In your own database, with row-level security and the access layer enforced server-side. The browser only ever holds a session token, never database or model credentials.
GET STARTED
If your last review ended with a search party.
The fix is not a bigger drive or an earlier email. It is evidence captured at source, tagged to the criterion it proves, with the numbers bound to it. Tell us which frameworks you report against and where the work breaks down today.