AI-FIRST · NOT AI-WASHED

Human depth.
Machine breadth.

We don't use AI to replace consultants — we use it to give them more reach. Three proprietary agents augment every Intoto engagement: Recon, Reasoner and Reporter.

See it in action →How it fits the methodology
The agents

Three roles. One engagement.

Each agent is purpose-built, sandboxed per-client, and never trains on your data.

RECON · AGENT

Surface mapping

Continuously enumerates your external and internal attack surface. Discovers shadow assets, forgotten endpoints, and supply-chain dependencies.

  • ↪ subdomain & ASN enumeration
  • ↪ JS/route extraction at scale
  • ↪ tech-stack & CVE correlation
  • ↪ certificate & DNS history
REASONER · AGENT

Hypothesis & chaining

Generates plausible attack paths from observed evidence and tests them in sandbox. Flags the chain — not just the dot.

  • ↪ exploit-path inference
  • ↪ low+low → high chaining
  • ↪ business-logic flagging
  • ↪ blast-radius estimation
REPORTER · AGENT

Remediation drafting

Produces engineer-ready remediation: reproduction steps, severity rationale, and code or config diffs in your stack's idiom.

  • ↪ CWE / OWASP mapping
  • ↪ PR-style fix suggestions
  • ↪ executive summary draft
  • ↪ Jira / GitHub export
The loop

Every machine output meets a human before it reaches you.

No AI finding ships unverified. Our consultants triage, validate, and prioritize every output. Where the agents excel is in volume and consistency — where humans excel is in judgment.

1
Agents propose.
Recon collects, Reasoner hypothesizes, Reporter drafts.
2
Humans validate.
Lead consultant reproduces, prioritizes, rewrites.
3
Clients ship.
Findings exported to your tracker, retests included.
// LIVE PIPELINE · ENGAGEMENT 0042
[14:02] recon: discovered 28 endpoints
[14:08] recon: 3 unauthenticated → flagged
[14:11] reasoner: hypothesizing IDOR /api/v2/orders
[14:14] reasoner: CONFIRMED: enum yields cross-tenant data
[14:14] human: reviewing finding...
[14:21] human: ✓ validated · severity raised to CRITICAL
[14:24] reporter: drafting fix · diff for OrderController#show
[14:29] human: ✓ shipped to client tracker
Data trust

Your data trains nothing.

AI-first does not mean data-loose. Every Intoto engagement runs in an isolated environment, with strict boundaries on what goes in, what comes out, and what's retained.

Per-engagement isolation

Each engagement gets its own ephemeral environment. No shared models. No cross-client context.

Zero training on client data

Client artifacts never enter our model training pipeline. Period. We use foundation models for inference only.

Encryption end-to-end

All artifacts encrypted at rest and in transit. Per-engagement keys, rotated quarterly.

Audit-grade logging

Every agent action is logged and reviewable. You can request the full chain of custody.

Destruction on close-out

Engagement environments and data are destroyed within 30 days of report delivery, unless you request otherwise.

Human-in-the-loop SLA

No finding leaves Intoto without consultant validation. Auto-publish to clients is disabled by design.

See the pipeline run on your stack.

We'll walk through a live engagement preview and answer the questions our diagrams won't.