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Sequrely · Agentic IAM for the age of AI

Enforcement you can audit.

An agent enforces identity policy at machine speed. Every decision stays inside your rules and on the record.

Server-side plaintext
0secrets
Client-side encryption
256bit AES
Policy model
3autonomy modes

Architecture facts and the policy model. Design targets are labeled where they appear.

HUMANS SSO / IDP AGENTS CLOUD IAM VENDORS SAAS CI RUNNER CONTAINED SOURCE SEQURELY

Illustrative identity graph. Live telemetry is shown in product.

Enforces across the stack you already run
SSO / IdPHRISCloud IAMSource controlCRMERPData warehouseTicketingCI runnersAI agents

System categories, not endorsements. The current connector list is available on request.

The problem

Identity is the new perimeter.

Credentials, sessions, service accounts and AI agents now outnumber the people who hold them. The auditor asks one question: who could do what, and who approved it.

The most expensive way in is a valid credential.

Most breaches start with a credential that was valid at the time. The login screen is taken seriously; everything a valid identity is allowed to do after it is not. The control that matters is what happens next.

$4.4Maverage cost of a breach

SOURCE: IBM · COST OF A DATA BREACH 2025GLOBAL AVERAGE

Machines outnumber people.

Service accounts, API keys, CI runners and AI agents hold more credentials than your workforce does, and most were never mapped to least privilege.

82:1non-human to human identities

SOURCE: CYBERARK · 2025IDENTITY SECURITY LANDSCAPE

Login is a binary decision.

One check, implicit trust after it, a blind spot until the session ends. Policy lives in a document, not in the session.

LEGACY MODELONE CHECK PER SESSION

Four consoles. Zero map.

IdP, HRIS, cloud IAM and SaaS admin panels each hold a slice of the truth. Nobody holds the join, so nobody can list every agent and what it can reach.

ENDPOINTS · CLOUDIDENTITY LOGS · NON-HUMAN

The auditor’s question.

Who could access what, when, and who approved it. Most estates answer in spreadsheets, weeks after the fact, from logs that were never meant to be evidence.

WHO · WHAT · WHENWHO APPROVED
Bounded autonomy

Watch a decision get made.

Low-risk actions execute at machine speed. High-risk actions wait for a human. Every row is sealed.

Illustrative investigation ledger. Example row: 09:41:02, Sequrely agent, Ended idle session · svc-payroll-bot · idle 31m, status Revoked.

# policy envelope · illustrative
version: 3
observe_before_enforce: 14d
machine_speed:
  - end_session:        { when: idle > 30m }
  - rotate_credential:  { when: share.expired }
  - contain_identity:   { when: drift.score > 0.9 }
checkpoint:
  - grant_jit_access:   { ttl: 2h, approver: org.owner }
  - add_device:         { approver: master_device }
human_gated:
  - delete_identity
  - export_vault
  - widen_scope
  - change_policy
ledger: sealed        # sha-256 chain of custody

Illustrative ledger and policy envelope. Syntax shows the policy model, not a shipping file format. The agent is in research; status is on the Platform page.

How bounded autonomy works

Four steps from map to evidence.

The agent never decides how much autonomy it has. You do, once, in a policy it cannot edit.

  • Machine-speed autonomous within policy
  • Checkpoint approve and audit
  • Human-gated always a person
  1. Map every identity

    Humans, service accounts, vendors and AI agents, mapped to the systems they can reach. The baseline is observed before anything is enforced.

  2. Set the policy envelope

    Decide which actions run at machine speed, which pause at a checkpoint, and which always wait for a human. The envelope is versioned.

  3. Enforce within it

    Stale sessions end, expired shares rotate, drift is contained. Anything outside the envelope stops and asks.

  4. Hand over the evidence

    Every decision, automatic or human, is sealed with a chain of custody. Export it when the auditor asks.

Server-side plaintext
0secrets
Client-side encryption
256bit AES
Policy model
3autonomy modes
Time to respond
22sec
from hours · design target

0, 256 and 3 describe the architecture and the policy model it enforces. 22 seconds is the design target for autonomous triage inside the policy envelope: illustrative, not a customer result.

Request a demo
Use cases · design

What the enforcement model is built for.

Three outcomes the map, the envelope and the ledger are designed to deliver without new infrastructure.

Inventory and visibility

Map every human and non-human access point to the finance, HR and engineering systems that matter, and capture a day-one snapshot of your risk posture.

DAY ONESNAPSHOT

Just-in-time access

Vendors, auditors and contractors get task-scoped access with an expiry. When the task ends, the access ends and the record stays.

SCOPEDAUTO-REVOKED

Shadow-AI remediation

Find the AI tools and agents nobody approved, bring them under policy, and leave no orphaned account or unmanaged agent active.

NON-HUMANLEAST PRIVILEGE

Status: time-limited sharing with an audit trail is available today; the identity map, just-in-time policy and shadow-AI inventory are designs. Current status is on the Platform page.

Access under control.
Audits without panic.

Thirty minutes on your estate, your audit calendar and the policy envelope you would set first.

Audit-ready evidence for SOC 2 and ISO 27001 controls. GDPR and HIPAA data-residency ready by architecture. Client-side AES-256; keys stay on your devices.