Who Dokima suits
Dokima vs conventional SAST
Rules are good at finding known patterns. Context changes the questions you can ask.
SAST is fast, repeatable and valuable in the development pipeline. Dokima is designed for deeper, codebase-aware review and a smaller set of findings carried through challenge and validation.
Where it works well
Conventional SAST has a useful job to do.
- Checking large volumes of code quickly and consistently.
- Finding recognised insecure patterns and data flows.
- Giving developers early feedback inside the development pipeline.
- Applying policy and language-specific rules at scale.
Where Dokima differs
Context and review, not just another pass.
- 01Dokima first builds repository, component and security-assumption context.
- 02Focused hunting stages can reason about intent and behaviour beyond a fixed rule catalogue.
- 03Candidate findings go through peer review, information gathering, validation and deduplication.
- 04The output is organised as a developer-readable security report, not a raw alert stream.
Capability comparison
CapabilityDokimaConventional SAST
Primary methodContextual, staged AI source reviewRules, patterns and program analysis
SpeedLonger, depth-oriented passesFast, frequent feedback
Codebase contextPersistent repository and component contextVaries; commonly centred on detectable code paths
OutputReviewed findings with evidence and remediationMatches and data-flow results to triage
DeterminismModel-dependent analysis with validation stagesTypically repeatable for the same rules and code
Use them together
Keep fast SAST checks in the pipeline. Use Dokima for deeper review, security assumptions and findings that need whole-codebase context.
See what Dokima finds
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