CPL Assessments

We are KnowMeQ, and ArchieCPL is our AI-powered Credit for Prior Learning (CPL) / Prior Learning Assessment and Recognition (PLAR) platform.

ArchieCPL is the most trusted, accurate Credit for Prior Learning platform.

ArchieCPL is AI-supported and human-led, built for institutional control:

• Powered by AI with a human in the loop
• Humans make final credit approval decisions

ArchieCPL is designed to help colleges and universities:

• Scale PLAR/CPL to handle high volumes of applications without proportionally expanding staff workload
• Make faster, more consistent, well-documented credit decisions while keeping academic control with the institution
• Support enrolment priorities by showing adult learners and other applicants how their prior learning can count toward a credential

Moving CPL to the top of the enrolment funnel

Traditional CPL/PLAR is often introduced after a learner has applied, been admitted, or registered. ArchieCPL flips that model by moving prior-learning discovery to the top of the recruitment funnel.

ArchieCPL helps prospective students understand what their previous work, military, education, and life experience may be worth before they choose a program, college, or pay for a formal review.

Through ArchieCPL and its white-label Marketplace, colleges, regions, and higher education systems can turn CPL from a back-office administrative process into a recruitment, enrolment, and revenue-generation engine for adult learners.

Why ArchieCPL is different

Registered students vs. prospective students

Search for a program vs. start with your experience

Traditional recruitment often expects learners to know what program they want.

ArchieCPL lets learners start with what they already know. A learner can upload a resume or connect LinkedIn, and ArchieCPL can identify:

This creates a more personalized and relevant recruitment experience.

Apply first vs. discover first

Traditional sequence:

ArchieCPL sequence:

Learners can see the value of returning to college before they commit.

Guesswork vs. confidence-guided decisions

Each course and program surfaced through ArchieCPL can include a percentage confidence measure indicating the strength of the match between the learner’s experience and the relevant learning requirements.

Example:

• Course Match: 86%
• Program Match: 78%

The score does not award credit. It helps learners understand where a formal CPL application is most likely to be worthwhile.

One college vs. regional discovery

On an individual college website, ArchieCPL can present opportunities from that institution.

Through a white-label regional Marketplace, learners can explore matching programs and courses across multiple participating colleges, including institutions within a selected geographic distance.

Traditional CPL asks:

The Marketplace asks:

The funnel shift (traditional vs ArchieCPL)

Traditional CPL funnel

Registered students

↓

Students who know CPL exists

↓

Students who investigate it

↓

Students who apply

↓

CPL applications

ArchieCPL funnel

Prospective students + workers + adult learners + career changers + Veterans

↓

Resume / LinkedIn analysis

↓

Course and program discovery

↓

Potential CPL discovery

↓

Confidence-guided decisions

↓

CPL applications

↓

College applications

↓

Enrolment

Traditional CPL begins near the bottom of the funnel. ArchieCPL begins at the top.

Smarter economics for institutions

Traditional CPL can require significant manual administrative and academic effort.

ArchieCPL automates major components of:

• prior-learning interpretation
• course and program matching
• confidence scoring
• evidence organization
• application preparation
• workflow management
• payment processing

The result is a model where CPL volume can grow without requiring equivalent growth in staffing.

CPL as a revenue opportunity

ArchieCPL can process paid CPL applications and support configurable revenue-sharing models with participating institutions or regional review partners.

Instead of CPL being viewed only as a processing cost, each CPL interaction can become:

The downstream value can include:

The ArchieCPL Marketplace model

A white-label ArchieCPL Marketplace gives a community, region, or higher education system a shared way to attract adult learners.

Instead of every college separately building technology and marketing programs, the region can market a shared proposition:

This creates shared infrastructure for:

• adult-learner recruitment
• prior-learning recognition
• program discovery
• college matching
• CPL applications
• payment processing
• regional pathway development
• enrolment intelligence

Strategic comparison

Measured outcomes (KnowMeQ internal program data)

KnowMeQ measures outcomes using our applicant, credit-award, and processing-time data. In our comparison data, ArchieCPL shows two measurable benefits:

• Average CPL awarded per individual applicant: 4 credits (compared with 1 credit in our comparison data)
• Staff processing time per file: reduced by 95%

How ArchieCPL search results differ from typical CPL searches

When ArchieCPL is accessed through a college’s website, it helps prospective and current students discover courses their experience may qualify them for.

ArchieCPL search results are designed to be actionable and reviewable:

• Student-facing discovery shows course matches and confidence scores to help a student decide which CPL applications are most worthwhile.
• Reviewer-facing results include the evidence and tools needed to make an informed decision.
• Institutional staff retain final approval authority.

Connecting the outcomes to institutional financial measures

Institutions often evaluate CPL modernization based on measurable operational and financial outcomes.

ArchieCPL can connect to two primary levers:

• Retention and tuition impact: recognizing more prior learning can make completing a credential more achievable. Institutions can measure retained enrolments, subsequent course registrations, and associated tuition revenue from the remaining courses students take.
• Staff capacity and cost: faster processing reduces labour required per review and can free staff capacity to support more applicants. Institutions can measure staff hours saved and changes in throughput.

Regional upskilling and adult learner recruitment

ArchieCPL can also serve as a gateway to regional upskilling. Governments, outplacement organizations, and employers can help workers identify where their existing experience may count toward college credit and which additional courses could support their next career step.

This can create opportunities for colleges to attract adult learners and develop employer-sponsored training pathways.

ArchieCPL for Veterans

ArchieCPL is designed to help Veterans and military-connected learners understand how military training, service experience, credentials, academic learning, and work experience may translate into postsecondary credit and shorter pathways to completion.

Combined with KnowMeQ’s skills and career intelligence, the same evidence can also be articulated into civilian skills, occupations, employment pathways, and targeted upskilling to support career mobility.

Why this matters

Veterans often leave military service with substantial learning and capability that can be difficult to see in civilian systems. Military occupations, rank, training, Joint Services Transcript (JST) records, credentials, and service experience can contain evidence relevant to postsecondary programs and civilian careers, but that evidence is frequently expressed in different language and data structures.

ArchieCPL is designed to create a bridge between those systems by:

• ingesting military and civilian evidence
• structuring the information into skills and learning outcomes
• comparing it with institutional programs and courses
• surfacing potential CPL opportunities for authorized human review

Veteran capability overview

Core functional workflow (Veteran education and credit recognition)

Potential institutional outcomes

• More consistent interpretation of military learning across programs and reviewers.
• Earlier visibility into potential CPL before a Veteran commits to a program.
• Reduced manual effort spent locating, comparing and documenting evidence.
• Better auditability through evidence traces, confidence indicators and decision rationale.
• Reusable precedents that can support future reviews where institutional policy permits.
• Shorter, clearer pathways for Veterans whose prior learning already meets course or program outcomes.

Skills taxonomy and military-to-civilian translation

A central challenge in Veteran mobility is that military, postsecondary and workforce systems describe capability differently. KnowMeQ’s underlying skills intelligence bridges those systems through a shared language of skills, competencies, tasks and evidence.

Connecting education recognition to career mobility (Johari Suite)

Veterans often need to answer two questions at the same time:

• “What can my military experience count for in college?”
• “What can my military experience qualify me to do in the civilian workforce?”

KnowMeQ’s architecture is designed so the same underlying profile can support both.

Johari creates an adaptive skills and capability profile using information from resumes, military experience, credentials, employment history and validated skill and competency assessments. The platform can identify transferable skills, compare an individual’s profile with civilian occupations and employment opportunities, identify skill gaps, and recommend careers and educational programs that are accessible now or through targeted upskilling.

Representative Veteran journey

1. The user begins with a resume, JST, MOS, rank, training record, credentials or a combination of these sources.
2. The platform normalizes military experience and maps it to a transparent skills and evidence profile. Optional KnowMeQ assessments can refine the baseline.
3. Career intelligence identifies civilian occupations and jobs that are accessible now, accessible with targeted upskilling, or that require a larger transition.
4. ArchieCPL compares the Veteran’s JST, academic, work and volunteer evidence against participating college or university programs and course learning outcomes.
5. The Veteran can see potential education pathways and possible prior-learning credit before beginning a formal institutional review process.
6. An institution receives the evidence package, match rationale and confidence information for authorized human review.
7. The Veteran’s profile remains reusable as new credentials, learning, work experience or military records are added.

• Receive a structured recommendation linked to the relevant source evidence.
• See the course/program learning outcomes and the military or experiential evidence contributing to the match.
• Review confidence and evidence indicators rather than a black-box recommendation.
• Accept, reject, redirect or request further evidence based on institutional policy.
• Record rationale and maintain an auditable decision trail.
• Where permitted, reuse approved precedents to support consistent future reviews.

Explainability, human review and academic integrity

ArchieCPL is designed to make AI-supported recommendations transparent and reviewable. ArchieCPL is not intended to make binding academic decisions on behalf of institutions.

Responsible AI principles

• Ground recommendations in identifiable source evidence and institutional curriculum data.
• Use constrained AI functions for interpretation and matching rather than allowing an unconstrained model to issue binding decisions.
• Maintain model, prompt, configuration and decision traceability where applicable.
• Support human correction, override and escalation.
• Evaluate quality and monitor unsupported or low-confidence outputs.
• Keep high-impact academic decisions under authorized human control.

Security, privacy and accessibility

Veteran education workflows can involve personally identifiable information, military records, academic records and other sensitive evidence. Security and privacy controls therefore need to be built into the architecture, data model and operating procedures.

Integration and deployment

ArchieCPL is designed as reusable intelligence infrastructure that can be integrated with enterprise platforms or delivered as a white-labelled cloud solution.

Representative integration points

• Student information systems (SIS) and institutional records.
• Admissions, advising, registrar and CPL/PLA workflows.
• Learning management systems and course/program catalogues.
• Credential and transcript sources, including JST and academic records.
• Career and workforce platforms.
• APIs and data feeds for program, course, learning-outcome and equivalency information.
• Reporting, audit and analytics environments.

Existing functional foundations

What success looks like

A successful Veteran skills-recognition workflow should make military learning easier to understand, easier to evaluate and easier to carry forward into both education and employment decisions.

White-label, public-facing experience (optional)

ArchieCPL can be deployed as a white-label solution for colleges and universities.

Depending on your implementation goals, it can:

• Reside on your institution’s website as a publicly accessible experience
• Help individuals explore programs to enroll in programs at the institution and for current students, to earn prior learning credits
• Commonly available resources are used to articulate the individual's skills and experiences: resumés, transcripts, work experience.
• ArchieCPL presents potential courses and programs that they may pursue at the institution and confidence scores act as a supportive guide for the individual to gauge the likelihood (via %) that they will qualify for a course credit application
• Applicants receive course and program recommendations for free. They only pay when they process formal CPL / PLAR course applications
• KnowMeQ and Colleges split ArchieCPL course application revenue; helping institutions recover subscription costs
• ArchieCPL as a state or regional marketplace: networks of colleges can use ArchieCPL and Eddie/Ed-T (Credit Transfer) for geographic credit mobility networks; applicants and students can identify where their credits can transfer, and where they may earn CPL credits (different programs or courses)
• Individuals' work, military and education experiences align to course and program outcomes, then organize the file for staff and faculty review

Our goal is to help institutions reinforce a simple learner message: “anyone can start here.”

How an ArchieCPL assessment flows

Our assessment moves through four stages, and each stage has a defined hand-off to a human reviewer.

• Submission: The student logs in, uploads a resumé, and picks the courses they want assessed for prior learning credit. College staff (registrar, credit transfer officers, or advisors) can request additional proof or pull in course-specific tests and quizzes.
• AI analysis: Our AI automatically assesses eligibility for course credit by comparing the resumé against the institution's own curriculum and learning outcomes. The assessment takes minutes.
• Recommendation Report: The AI generates a report for staff review that includes a confidence score, a written rationale explaining the matches between the student's evidence and the course outcomes, and color-coding so reviewers can triage strong, marginal, and weak cases quickly.
• Review and decision: College staff (and, depending on the institution, faculty and chair-level reviewers) accept, reject, or request further evidence. Approved credits are pushed to the institution's Student Information System (SIS) for posting on the student transcript.

Scoring rubrics for prior learning

Our scoring is not a single pass/fail check. Instead, our AI matches the student's evidence against comprehensive skill and competency taxonomies tied to each institution's stated learning outcomes, and it returns a confidence score plus a detailed rationale that tells reviewers why a particular score was assigned.

To protect the integrity of the score, we include built-in safeguards in the validation step:

• Color-coded outputs to flag strong matches versus weak matches for triage.
• AI-generated content detection so reviewers can see when uploaded artifacts may have been synthesized rather than produced by the learner.
• Request-for-further-evidence pathways that let staff trigger follow-up artifacts when the initial evidence is not enough to support a credit decision, including:

- reflection essays

- reference letters

- video submissions

- follow-up quiz questions aligned with course outcomes

When you (as an institutional customer) onboard, we configure the rubric to your specific programs so the AI is comparing evidence against your own learning outcomes, not a generic national standard.

Validation workflows with universities

We don't replace faculty review; we route submissions to it faster.

Our public case examples include three validation models that partner colleges use with ArchieCPL:

• Hybrid review (Fleming College): Fleming uses a hybrid approach where AI handles speed and scale while subject matter experts (SMEs) supply the human judgment that protects assessment integrity. Fleming's white-labeled implementation is called FastPass, launched in November 2024. In its first phase, FastPass generated more than 5,000 unique course recommendations.

Across all of these models, our AI’s role is to surface the recommendation and rationale; the human reviewer’s role is to decide and sign off.

Credential equivalency mapping

Equivalency mapping is the step that converts an assessment into an actual credit decision.

ArchieCPL maps the skills, certifications, and work history it identifies against standardized learning outcomes and against your institution-specific learning outcomes. Each match is captured with enough detail that faculty can accept it, reject it, or request further evidence on its merits.

For institutions that want a public-facing equivalent, we can support practices that pair a transfer-rule database with an online equivalency tool on the partner's own website. We can configure ArchieCPL to support either an internal-only mapping workflow or a hybrid that also publishes approved equivalents to students and advisors.

Transcript-level reporting

Once a credit decision is approved, our workflow produces the artifacts your registrar needs to post credit on a transcript:

• Recommendation Reports generated by the AI, which record the evidence reviewed, the matched learning outcomes, and the confidence score at the time of the decision.
• Decision records stored in your institution's credit transfer database so the same prior learning can be re-evaluated consistently across terms and across applicants.
• SIS push of approved credits so they appear on the student transcript without manual data entry by the registrar.
• Automated transcript request and retrieval support for institutions that want CPL students to have their existing transcripts pulled and matched as part of intake.

The intended end state is that credit decisions and the evidence behind them are reproducible: another reviewer, working the same file in a later term, can see exactly what was considered and why.

Strategic fit: PLAR/CPL as an enrolment priority

ArchieCPL is a scalable credit recognition platform that helps colleges and universities expand PLAR/CPL as a strategic enrolment priority.

It’s especially relevant for:

• Adult learners
• Workers and mid-career learners
• Newcomers
• Career changers
• Learners with prior education or significant prior experience

By helping applicants see that their previous learning, work, and life experience can count toward their next credential, institutions can improve application confidence, conversion, and persistence.

Integration-ready

ArchieCPL can be designed to connect with institutional systems based on your implementation priorities, including:

• Student Information Systems (SIS) for transcript posting
• CRM platforms to support enrolment pipelines
• Application workflows and other institutional intake processes
• Credential/credit transfer tools (where applicable)

Core value (most important points)

1. Scalable PLAR/CPL capacity: Expand PLAR/CPL volumes without proportionally expanding staff workload, while keeping academic review and final decisions in institutional hands.
2. Labour efficiency: Reduce manual file review by 90% - organizing resumés, transcripts, evidence, work experience, and learning outcome alignment in one place.
3. Trust and academic control: We do not position ArchieCPL as an automatic credit-awarding system. It supports the review process with structured evidence, alignment indicators, confidence signals, and audit trails, while the institution retains academic authority.
4. Cost-effective enrolment strategy: Use PLAR/CPL as a student access tool and an enrolment conversion tool by helping adult learners see that their previous learning has value.
5. Student access and confidence: Reduce uncertainty around fit, recognition of experience, and time commitment by giving learners a clearer starting point and a more navigable, responsive experience.
6. Workforce alignment: Support employer partnerships, upskilling pathways, workforce development, and mid-career recruitment by translating workplace learning and experience into academic pathways.

Pairing with transfer credit workflows (Eddie/Ed‑T)

ArchieCPL supports prior learning credit. It can also work alongside Eddie/Ed‑T for transfer credit and equivalency workflows.

Together, they can support a broader credit mobility strategy for learners entering college from work, other institutions, military experience, or non-linear education pathways.

International research: CPL practices in Canada and the USA

KnowMeQ has completed international Credit for Prior Learning (CPL) research outlining practices of key institutions in Canada and the USA.

How ArchieCPL helps institutions (benefits and outcomes)

Increases revenue and enrolment

• Nearly 4 in 10 employees (37%) are concerned their current skills will become obsolete in the future, and 64% of respondents say upskilling and reskilling has been useful for their job security.
• Employers anticipate that 44% of workers’ skills will be disrupted in the next five years, with 6 in 10 employees requiring training and upskilling before 2027.
• 71% of adult learners highlight flexibility as a crucial factor in their educational pursuits.
• Students allocated credit for prior learning saved an average of 9 to 14 months in earning their degrees and between $1,500 and $10,200 in tuition costs (depending on the institution type).

Improves student retention

• Adult students with prior learning credits had a credential completion rate of 49%, compared to 27% for non-PLA adult students.
• Receipt of CPL is associated with a 17% increase in the likelihood of completing a credential.
• Adult students who earned credit through Prior Learning Assessment (PLA) took, on average, 17.6 more course credits from their institution compared to those without PLA credits.

Optimizes institutional resources

• AI usage in higher education has surged 2.3x over the past year, with 93% of leaders expecting even greater use over the next two years.
• 80% of higher-education respondents are adopting AI to boost efficiency and productivity across their institutions.
• Over 80% of administrators predict significant growth in AI use for student success, enrollment management, and marketing.

Strengthens workforce alignment

• CPL recipients have a 17% higher employment rate within six months of graduation and earn 10–20% more annually than non-CPL peers.

Executive summary (higher-education context)

Higher education is facing a financial crisis that is driving job losses, program cuts, and projected deficits. At the same time, technological advances are making reskilling and upskilling more important than ever.

According to the World Economic Forum’s Future of Jobs Report 2025, employers anticipate that 39% of workers’ core skills will need to change by 2030.

Implementing ArchieCPL: a roadmap for success

Phase 1: Organizational alignment

• Conduct cost-benefit analysis and define institutional goals.
• Secure stakeholder buy-in through faculty, administration, and student engagement.
• Ensure compliance with privacy regulations (FERPA, GDPR, PIPEDA).

Phase 2: Pilot and integration

• Integrate with existing student information systems (SIS).
• Run a pilot program with a department or faculty.
• Optimize workflows and train admissions teams.

Phase 3: Full-scale adoption and growth

• Expand AI-powered credit recognition campus-wide.
• Develop marketing and recruitment campaigns targeting experienced learners.
• Establish feedback loops to continuously improve system performance.

Introducing ArchieCPL

What is ArchieCPL?

Built with Canada’s Vector Institute for AI, ArchieCPL is informed by skill and competency taxonomies that are internationally recognized and creates through-lines between occupations, postsecondary programs, and learning outcomes.

ArchieCPL’s AI platform assesses postsecondary students’ Credit for Prior Learning applications quickly, reducing bias. It allows higher-education institutions to process 10x the number of course-credit applications without increasing headcount, creating valuable new revenue opportunities for universities and colleges.

How it works

1. Applicant uploads their resume or transcript to Archie.
2. Archie’s AI evaluates skills, education, and experience vs. postsecondary programs and course learning outcomes for credit recognition.
3. Student receives prior learning credit recommendations, along with a confidence / predictor of credit application success percentage instantly.
4. Student meets with a college administrator to review the application and receive credit approval.
5. Student’s course credits received through ArchieCPL are added to the academic transcript.
6. Student begins a faster, less expensive postsecondary journey.

Why KnowMeQ

• Deep higher-education expertise — our solutions are designed with academic rigor and industry best practices.
• Unmatched AI-powered accuracy — built on proven machine learning models trained on education and workforce data.
• Seamless integration — colleges have the option to plug ArchieCPL into their existing SIS, CRM, and LMS platforms, and complement their workflows.
• Dedicated implementation and support — our team provides white-glove service to ensure seamless adoption and continuous success.

Getting started

If your college wants to run a CPL pilot on ArchieCPL, the next step is a working session with our team. We walk you through configuration of the rubric to your outcomes, set up the validation routing for your faculty, and map your SIS handoff.

• Product page: https://knowmeq.com/archie-cpl
• Request a demo: https://calendly.com/matt-foran-knowmeq-sm/meet-archie

You can also reach us at hello@knowmeq.com.