Learning Analytics & Assessment

We build assessment and analytics that help educators understand what learners can demonstrate, where they struggle and how a programme can improve. The work combines competence-based rubrics, learning-event data and clear reporting, with human review for consequential assessment decisions and validation before predictive models are used.

Every team member at Krazio is AI-enabled and tech-certified, to ensure your project is delivered quickly and as expected.

Services We Offer

Comprehensive solutions tailored to your business needs

Competence-based assessment

Design practical tasks and rubrics aligned with the programme’s learning objectives.

Marking support

Assist reviewers with structured evidence and feedback while retaining human oversight.

Learner support signals

Evaluate patterns that may indicate a need for support, with documented limits and validation.

Cohort dashboards

Show performance, progression and programme trends using agreed definitions.

Learning-event pipelines

Connect activity from supported learning tools to a consistent event and reporting model.

Audit-ready reporting

Document assessment criteria, evidence and review history for programme governance.

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Business Solutions We Provide

Industry-specific solutions that drive real business value

Evidence beyond completion

Understand demonstrated skills alongside attendance or course completion.

Targeted learner support

Help educators identify areas needing attention and plan appropriate follow-up.

Consistent review

Use documented rubrics and review workflows across assessors.

Programme improvement

Compare modules and cohorts to guide curriculum revisions.

Let’s Build Something Brilliant with Learning Analytics & Assessment

Whether it’s Learning Analytics & Assessment or a custom solution tailored for your business, we’re ready to make it happen. Tell us a bit about your idea, and our team will get back within 24 hours with a plan designed just for you.

The Core Problems We Solved

"Completion reports provide limited evidence of demonstrated competence."

"Learner difficulties become visible only after a course has ended."

"Richer assessments are hard to review consistently and efficiently."

What We Deliver

Assessment framework

Agreed tasks, rubrics and review workflow.

Data and reporting pipeline

Validated event mappings and dashboards for the agreed measures.

Evaluation evidence

Documented data checks and model or rubric validation findings.

Operational handover

Source, documentation, access roles and maintenance guidance.

Our Approach & Key Features

Assessment first

Define the skill, evidence and scoring criteria before designing dashboards.

Data quality

Check event consistency, missing data and interpretation before analysis.

Validation and fairness

Evaluate model and rubric performance for the intended population and use.

Human-led decisions

Keep consequential grading and support decisions under responsible human review.

Why Choose Krazio

Assessment design and meaningful evidence guide the reporting model.
Predictive features are evaluated on the available data before being proposed for use.
Documentation explains criteria, limitations and the review responsibilities of the education team.
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Rahul Bhatt

Rahul Bhatt

CEO & Founder

A LEADERSHIP MESSAGE ON LEARNING ANALYTICS & ASSESSMENT

"At Krazio, our vision is to empower businesses with cutting-edge technology that drives growth, efficiency, and innovation. We are committed to delivering excellence."

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Our Process

Step 1

Scope

Agree learning outcomes, decisions and the evidence required.

1
Step 2

Model

Define rubrics, events, data sources and reporting measures.

2
Step 3

Build and validate

Implement workflows and evaluate data quality, scoring and reporting.

3
Step 4

Deploy and review

Train the team and agree monitoring and periodic assessment review.

4

Frequently Asked Questions

Everything you need to know about our learning analytics & assessment services

Can AI support free-text marking?
How early can learner difficulties be identified?
Can data come from multiple learning systems?
Can this support accreditation reporting?

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Words of Appreciation

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