01
Connect
Bring in learning data through files, APIs, databases, xAPI streams, SFTP, cloud storage, and system-specific connectors.
LMS · HRIS · SIS · LRS · Content · Assessment · BIArcs Learning Intelligence Platform
Turn disconnected learning systems into connected intelligence.
Connect learning data across LMSs, HRIS, SIS, content, assessment, and experience systems. Arcs normalizes, governs, and activates it for migration, reporting, compliance, integration, and AI, without replacing the systems you already use.
Why the platform exists
Your learning systems were never designed to work as one.
Learning records and context are spread across platforms, file exports, data stores, content tools, and business systems. Each source uses different identifiers, fields, definitions, and rules. The result is slow reporting, risky migrations, incomplete audit evidence, and AI working from partial context.
Arcs sits behind the systems you already use, brings data into one normalized model, preserves source lineage, makes quality issues visible, and gives people and systems a governed way to use the records.
Your data is the asset. The platform is not.Arcs keeps learning data portable and useful as LMSs, vendors, reporting tools, and AI systems change.
How Arcs works
Connect. Govern. Activate.
Arcs creates one continuous path from fragmented source data to trusted learning intelligence.
02
Normalize and govern
Map source fields into a single normalized model, preserve lineage, surface quality issues, reconcile identities, and validate every stage of the record flow.
Learners · Courses · Enrollments · Completions · Scores · Certifications · Paths · Metadata03
Activate
Use governed data for analytics, audits, migrations, outbound integrations, business workflows, and AI grounded in trusted learning context.
Reporting · Compliance · Migration · Integration · Skills · AIConnect
Connect the systems you already have.
Start with the path your data supports today, from a practical file export to a scheduled API or database connection. Arcs brings each source into one governed ingestion process while keeping credentials, sync settings, detected objects, and connection health visible.
- Support file-based, database, API, xAPI, SFTP, and cloud-storage paths.
- Test connections and inspect schema coverage before a production sync.
- Maintain visibility across every source without locking your data into a single vendor ecosystem.
Normalize and Validate
Turn messy exports into governed dataflows.
Arcs detects likely entities and mappings, shows sample values and confidence, and flags duplicate targets, missing fields, and transformations inline. Teams can review what will happen before any record reaches the governed model.
- Group related files for learners, courses, enrollments, completions, scores, and certifications.
- Review suggested mappings with confidence and sample data.
- Save repeatable mapping logic for future imports.
Ingest
Trace every learning record.
Ingestion should not be a black box. Arcs shows what was extracted, loaded, normalized, deduplicated, quarantined, rejected, and placed in the warehouse. Source history and validation checkpoints remain visible so teams can investigate exceptions before treating the data as trusted.
- Track record flow and parity from source through the warehouse.
- Separate harmless warnings from migration-blocking issues.
- Preserve source history and quality states for review and auditability.
Explore
One learning model across every source.
Browse learners, courses, activities, enrollments, completions, scores, assessments, certifications, learning paths, content, groups, permissions, and metadata without losing the connection to their source systems.
- Use learning-specific entities and relationships instead of a generic data table.
- Filter and inspect records with source and validation context attached.
- Create saved views and export governed records when needed.
Analyze
Build reports people can trust.
Arcs turns the normalized model into analytics with visible definitions, filters, freshness, source coverage, and supporting records. Leaders get a coherent view, while analysts can still inspect what sits behind each metric.
- Compare learner activity and outcomes across contributing systems.
- Move from summary metrics to the records that support them.
- Feed governed data into Arcs views or the BI environment already in use.
Reconcile
Add the context that learning data lacks.
Learning activity becomes more useful when the right learner is connected to the right employee, student, role, program, term, or group. Arcs makes identity matching visible, confidence-based, reviewable, and reversible instead of hiding it as a backend assumption.
- Reconcile LMS identities with HRIS or SIS records.
- Auto-match high-confidence records and queue ambiguous matches for review.
- Export a governed crosswalk with match method and status.
Activate
Move normalized data out safely.
Arcs supports controlled system-to-system movement when learning data needs to reach a surviving LMS or another destination. Teams can configure mappings, run a dry run, review exceptions, require approval, execute with explicit permissions, and retain validation evidence.
- Separate configuration, simulation, approval, execution, and validation.
- Surface blocking exceptions before a live write.
- Produce a clear record of what moved and what requires attention.
What the data layer makes possible
Solve the immediate problem. Keep the value working.
Arcs can support a focused migration or integration project without requiring a broader platform commitment. When the normalized data remains in the platform, it becomes a durable foundation for more use cases.
Safer LMS change
Extract, map, validate, and move learning history without letting the destination platform decide what institutional memory you keep.
Cross-system reporting
Create one reporting foundation across LMSs and related systems, with consistent definitions, visible source coverage, and drill-down to supporting records.
Audit-ready evidence
Keep completion, certification, content-version, role, and source context available even as systems change.
Identity and capability context
Connect learning activity to the employee, student, role, program, group, or skills framework that gives it meaning.
Managed integration
Keep learning data moving among LMS, HRIS, SIS, BI, compliance, content, and workflow systems as the stack evolves.
Grounded AI
Give assistants and agents governed learning context instead of asking them to reason from disconnected exports and incomplete records.
Built for governed enterprise work
Control should be visible, not assumed.
Learning data can include sensitive employee, student, compliance, and performance context. Arcs is designed to make access, data movement, record lineage, and high-risk actions explicit.
Roles and permissions
Define who can view, configure, review, approve, or execute work across sources, mappings, analytics, reconciliation, and outbound movement.
Credential and environment controls
Keep secrets out of the interface, separate production and staging, and make connection health and access requirements visible.
Lineage and auditability
Preserve source identifiers, quality states, transformations, match methods, job history, and validation evidence.
Review before action
Use confidence thresholds, exception queues, dry runs, approval gates, and explicit confirmation for high-risk writes.
Built for the people responsible for learning data
Learning operations leaders LMS and HRIT owners Migration and implementation leads Data and integration administrators Compliance owners Learning analysts
Best starting points
LMS migration or consolidation Historical record preservation Untrusted cross-system reporting Compliance evidence HRIS or SIS reconciliation AI-readiness and governance
Frequently asked questions
A neutral layer, built to fit the stack you have.
Is Arcs another LMS?
No. Arcs does not replace content delivery, enrollment workflows, or the learner experience in your LMS. It is the vendor-neutral learning intelligence layer behind your existing systems, where data can be connected, normalized, governed, and activated.
Do we have to replace our current systems?
No. Arcs is additive. You can start with one source, one migration, one reporting problem, or one integration and expand as the value becomes clear.
What kinds of data can Arcs connect?
The platform is designed for learning-specific records such as learners, courses, activities, enrollments, completions, scores, assessments, certifications, learning paths, content, groups, permissions, and metadata. Connection paths can include files, APIs, databases, xAPI streams, SFTP, and cloud storage.
Can Arcs help with an LMS migration?
Yes. Arcs supports the hard data work around migration and consolidation: source inventory, extraction, mapping, normalization, deduplication, identity matching, validation, controlled outbound movement, and preservation of history.
Can we use the data in our existing BI or AI environment?
Yes. The platform is intended to make governed learning data available to reporting, integration, and AI workflows without forcing the organization into one presentation layer or model provider.
Where should we start?
Start with the operational problem that already has urgency: a migration, an audit risk, a reporting gap, a fragmented integration, or an AI initiative blocked by unreliable learning data. Arcs can assess the landscape and define the smallest useful first step.
See what trusted learning data could unlock.
We will help you understand the systems, records, risks, and opportunities in your learning data landscape, then define the most practical path from fragmented data to governed action.
Start with a focused conversation about your systems, current pain, and the outcome you need.