Modern Software is Getting Harder.
Clarity Shouldn’t Require Enterprise Pricing.
AI-assisted coding is already part of everyday development. What’s changed is the level of detail teams need to stay confident in what they ship.
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That’s why SCANOSS starts with snippet-level matching — to surface reuse that doesn’t show up as components or dependencies.​
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Undeclared open source components
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Licence obligations at source-code level
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Known vulnerable code
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Unknown provenance and reuse patterns
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Why Existing Tools Fall Short
Most software supply chain tools were built for a world of declared dependencies and predictable reuse, and they struggle when development becomes faster, more fragmented, and AI-assisted. The result is familiar: high cost, heavy processes, and reports that still don’t fully explain what’s actually running in your codebase.
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That gap is why teams invest more and trust the results less.
Tools built for yesterday’s development can’t explain today’s code.
Works Where Your Teams Already Work
SCANOSS integrates into existing development and review workflows, including modern CI/CD and code review processes, without enforcing changes.
No enforced gates​
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Analysis does not block builds or deployments unless teams explicitly choose to enforce policies.
No workflow changes​
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No IDE plugins, no mandatory pipeline steps, and no changes to how developers write code.
No AI tool interference​
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Developers continue using AI coding tools as they do today.
Designed to fit modern CI/CD and code review workflows — without changing how teams work.
VISIBILITY
Expose open source code and reuse introduced through AI-assisted generation.
Know what entered your codebase.
TRACEABILITY
Understand where AI-assisted code comes from and how it relates to known open source projects.
Context matters when reuse is involved.
REVIEW
Support informed decisions with side-by-side comparisons and recorded outcomes.
Evidence first, judgement second.
From Inventory to Action
The inventory produced by SCANOSS supports review, documentation, and repeatability.
Once AI-assisted code is identified and reviewed, teams use the inventory to:
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Examine findings with full source-code context
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Record review outcomes and decisions
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Reuse those decisions across future scans to ensure consistency
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Provide concrete evidence during audits and internal reviews
SCANOSS focuses on exposing facts and preserving decisions, leaving judgement and enforcement with the organisation.
What it Enables
Assisted Code Audits
Review AI-generated contributions with verifiable evidence from source code, not assumptions.
Licence & IP Awareness
Expose undeclared open source reuse introduced through AI assistance before it becomes an issue.
Audit Traceability
Record and preserve review decisions to support internal audits and external assessments.
Consistent Practices
Apply the same evidence-based process to AI-assisted code across teams, projects, and releases.