Grego AI | How Grego AI Works

Deep invariant analysis

The most dangerous vulnerabilities live between the parts.

Grego turns complex software into a coordinated field of security investigations. Specialized agents follow interactions across components, state, permissions, and economic assumptions. Independent layers challenge candidates before they reach a researcher.

Explore the architectureFollow a research path
Illustrative interaction depthReasoning path
  1. L01Entry surfaceWhere behavior begins
  2. L02State gateWhat must already be true
  3. L03Privilege edgeWho can move the system
  4. L04Cross-component effectWhat changes elsewhere
  5. L05External assumptionWhat the system trusts
  6. L06ReachabilityWhether the path is real
  7. L07+Invariant breakWhere valid parts compose into failure
  • Repository-wide context
  • Thousands of focused research paths
  • Independent challenge
  • Traceable evidence

One system. Many research paths. One evidence chain.

A scan becomes a structured research program: assemble context, distribute focused work, trace system behavior, challenge candidates, and preserve what survives. Open any component to see why it exists.

Grego reasoning fabric

Control layer

Coordinates work and preserves boundaries

Context plane

Signals in

Reasoning environments

Parallel, repository-aware work
Investigative cells1…N paths
Focused research cellLocal context · shared source
  • Component interactions
  • State transitions
  • Privilege boundaries
  • Economic conditions

Evidence plane

Artifacts out

Assurance layer

Separate passes try to eliminate weak candidates
Review-ready findingsConsolidated evidence · impact · provenance
High-level Grego reasoning architecture from context and parallel investigation through assurance and review-ready findings.

From system context to defensible finding.

The geometry stays constant while the work changes: signals enter, a controlled reasoning environment transforms them, and inspectable evidence leaves.

Stage 01 / Frame

Bound the system before asking it to break.

Source, architecture, scope, and security knowledge are reconciled into a research context. Unknowns remain visible instead of being silently invented.

Signals

  • ArtifactSource and dependencies
  • ConstraintArchitecture and scope
  • IntelligenceSecurity knowledge

Controlled reasoning environment

Focused state
  • ControlContext assembler
  • ControlScope reconciliation
  • ContextAssumption register
  • EvidenceUnknowns ledger

Evidence

  • ArtifactBounded research context
  • ArtifactSystem map
Stage 02 / Expand

Turn one system into focused lines of inquiry.

The orchestrator decomposes the target into narrowly framed investigations and prioritizes hypotheses that fit each surface. Breadth grows without forcing every path into the same context.

Signals

  • ArtifactBounded context
  • IntelligenceSecurity taxonomy
  • ContextInteraction surfaces

Controlled reasoning environment

Focused state
  • OrchestrationPath decomposition
  • ReasoningHypothesis selection
  • OrchestrationPriority routing
  • EnvironmentCell initialization

Evidence

  • ArtifactPrioritized research paths
  • EvidenceCoverage plan
Stage 03 / Investigate

Trace the interaction, not only the line.

Repository-aware investigations follow calls, state changes, authorization boundaries, dependencies, and incentives. Every path stays focused while retaining the evidence needed to explain its conclusion.

Signals

  • Reasoning pathScoped hypothesis
  • ContextRelevant repository context
  • ConstraintSystem assumptions

Controlled reasoning environment

Focused state
  • Agent workRepository inspection
  • Agent workState-path mapping
  • Agent workInvariant reasoning
  • GateMid-path evaluation

Evidence

  • ArtifactCandidate violation
  • EvidenceResearch trail
Stage 04 / Falsify

Try to kill the candidate.

Independent validation asks whether the path is technically possible, realistically reachable, and meaningfully harmful. A failed gate becomes a recorded rejection, not a hidden success.

Signals

  • ArtifactCandidate report
  • EvidenceRepository evidence
  • ContextOperating constraints

Controlled reasoning environment

Focused state
  • VerificationTechnical challenge
  • VerificationReachability check
  • VerificationImpact check
  • VerificationIndependent review

Evidence

  • ArtifactValidated candidate
  • EvidenceRecorded rejection
Stage 05 / Converge

Resolve overlap. Preserve the strongest path.

Related candidates are clustered, redundant reports are collapsed, and complementary observations can be composed into a stronger attack path. Convergence reduces noise without discarding useful evidence.

Signals

  • ArtifactValidated candidates
  • EvidenceFinding relationships
  • ContextSeverity evidence

Controlled reasoning environment

Focused state
  • ReasoningSimilarity grouping
  • ReasoningBest-path selection
  • Agent workCross-report analysis
  • Agent workFinding synthesis

Evidence

  • ArtifactNon-duplicative findings
  • EvidenceCombined attack path
Stage 06 / Evidence

Give researchers the full evidence chain.

High-consequence findings can receive multiple independent reviews and a separate synthesis pass. The result adds guidance and provenance without silently rewriting the underlying report.

Signals

  • ArtifactSynthesized finding
  • ReviewIndependent analyses
  • EvidenceResearch lineage

Controlled reasoning environment

Focused state
  • VerificationIsolated review
  • ReasoningDisagreement resolution
  • EvidenceAdvisory signal
  • ArtifactProvenance packaging

Evidence

  • ArtifactReview-ready package
  • EvidenceResearcher guidance

Built-in opposition

The system is designed to disagree with itself.

Discovery and validation have different jobs. One layer searches aggressively for failure. Another tries to disprove the path. A third resolves overlap and evidence. Separating those objectives turns plausible narratives into testable claims.

Continuous reasoning loopEvery stage reads from and writes to the same evidence record.
  1. 01

    Scope the system

    Establish the system boundary.

  2. 02

    Explore hypotheses

    Generate competing research paths.

  3. 03

    Trace invariants

    Follow state and interactions.

  4. 04

    Challenge evidence

    Try to disprove each claim.

  5. 05

    Synthesize findings

    Consolidate what survives.

Shared evidence recordContext, decisions, uncertainty, and research provenance stay attached across the full cycle.Surviving evidence becomes context for the next research cycle.
  1. 01

    Breadth without context collapse

    Work is distributed across focused investigations instead of flattened into one oversized request.

  2. 02

    Depth without a monolithic prompt

    Each reasoning path retains local context while the underlying system remains explorable.

  3. 03

    Verification without self-certification

    Candidate generation and candidate judgment are separated by successive evidence gates.

  4. 04

    Scale without losing provenance

    Structured state preserves investigation-level and run-level lineage throughout the workflow.

Beyond code review. Toward system reasoning.

Frontier models are one component. The defensible advantage comes from the system around them: how context is assembled, work is decomposed, hypotheses are pursued, candidates are falsified, and evidence is preserved.

Grego is built to search the interaction space that traditional review cannot exhaust, then return the small number of paths that deserve expert attention.