Spot problems in your code and understand your project.

CoreAnalyzer analyzes your files, their structure and connections to produce a clear report, with findings and references for your teams or AI agents to verify.

Discovery and Essential: Web. Pro: Web, CLI and CI/CD; MCP in beta, on request.

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1 Import

Your source project

Select your project and review the files included in the analysis.

2 SOFTWARE MAPPING

Analysis and relationships

The deterministic engine examines the code and collects available signals, references and relationships.

3 Secure exports

Secure exports

Native .CDP, optional JSON, encrypted .CDP.

4 Final purge

Non-retention & final purge

Source files are purged after processing; reports follow the documented retention window for the selected workflow.

Incubated by TechForward

EDHEC · EURECOM · Institut Mines-Télécom

accompanied by NiceStartUp

A report to inspect, not just a score.

Review findings, locate their references and explore the relationships present. Keep the report to reopen, compare or share it according to your access rights.

Classic CoreAnalyzer report view
Classic reportBrowse results, categories, filters and file/line evidence.

A deterministic engine. Explicit boundaries.

PROPRIETARY ENGINE

Code analysis does not depend on an AI model.

CoreAnalyzer runs the analysis with a deterministic proprietary engine. AI agents can use the artifacts afterwards, without replacing the analysis itself.

NON-RETENTION

Documented, temporary processing.

Sources are processed temporarily. Report availability and cleanup depend on the workflow used.

Follow a finding back to the project.

Available context depends on the language, the code and the evidence collected. The report keeps what is established separate from what still needs verification.

  1. Locate the result

    Find its category, file and cited line. Check the analyzed scope before interpreting a total.

  2. Explore the available context

    Inspect the routes, symbols, dependencies or safeguards linked to the result when they are present.

  3. Decide what to verify

    Distinguish established evidence from assumptions that require source review, tests or runtime context.

See how to read a report

Explore the context with SAI.

SAI organizes the report already produced by CoreAnalyzer: application layers, available relationships and investigation paths. It does not run a second analysis.

Prioritize the review

Group results by layer, category and available context.

Find the references

Return to the cited files and lines to verify each result.

Reuse the report

Share structured context with your teams or AI agents. Quality and token savings remain to be measured.

Choose how you use CoreAnalyzer.

The same engine and report views. Plans vary volumes, exports and access channels, not analysis quality.

Target audience:

For Web, CLI and CI/CD. MCP is in beta, on request and by invitation.

Included exports:

Native .CDP, JSON, encrypted .CDP, PDF/HTML/CSV

  • Up to 100 analyses per month · 1 active project
  • Up to 50 MB of source code, config and infra files — binary assets excluded.
  • Web, CLI and 1 CI/CD integration on request
  • Advanced exports; MCP beta on request
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Start with a project you know.

Review the findings and references to assess what CoreAnalyzer adds to your review.

Try it on the WebSee the reports