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Identity-First Security Platform

Every AI Initiative
Stands on One Thing:
Identity.

The identity-first security control plane for organizations deploying AI — unifying human, machine, and agent identities under one policy, one source of truth, one auditable foundation.

See How It Works
UNIFIED REGISTRY 👤 HUMAN ⚙️ SVC ACCT 🤖 AGENTS 📦 WORKLOAD 🔑 API KEY 🏢 CONTRACTOR
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More machine identities than human ones in the average enterprise
0%
Of breaches involve a compromised or overprivileged identity
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Audit cycle reduction when evidence is generated continuously
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Identity coverage — humans, machines, and AI agents unified
The Foundation

One Identity Fabric for Humans, Machines, and AI Agents

Most organizations manage three identity populations in three disconnected silos. foundation.ms unifies them — a single registry of who and what exists, least-privilege enforcement across all three, and an audit trail that regulators and security teams can rely on. Instead of bolting identity controls onto each new AI project, you deploy projects onto a foundation where the controls already exist.

👤
Workforce Identities
Employees and contractors with role-based, scoped access
Governed
⚙️
Machine Identities
Service accounts, workloads, API keys, model endpoints
Governed
🤖
AI Agent Identities
Every agent registered with declared purpose, owner, permissions
Governed
ONE POLICY. ONE SOURCE OF TRUTH.
Uniform enforcement across cloud, on-prem, and AI infrastructure.
Core Capabilities

Built for the Identity Layer Everything Else Runs On

Six foundational controls, applied uniformly across every identity in your environment.

🗂️
Unified Identity Registry
A single, authoritative inventory of every identity in your environment — employees, contractors, service accounts, workloads, and AI agents — with ownership, purpose, and lifecycle status for each. Unknown identities made impossible.
🔒
Least Privilege by Default
Access granted on a deny-first basis, scoped to the minimum each identity requires. Policies follow the identity across clouds, applications, and on-premises systems, so privilege never silently expands as infrastructure changes.
🤖
AI Agent Governance
Agents registered as first-class identities with a declared purpose, an owner, and explicit permissions. Every agent action is attributed and logged — so "the system did it" is never the final answer in an audit.
🔄
Continuous Verification
Trust is never assumed and never permanent. Identities are re-verified continuously against behavior, device posture, and context — zero-trust applied uniformly to people and software alike.
🛡️
Privileged Access Controls
High-risk credentials vaulted, rotated, and checked out just-in-time rather than standing open. Privileged sessions are recorded and monitored, collapsing the window in which a stolen credential is useful.
📋
Audit-Ready Evidence
Every access decision, grant, and revocation captured in a tamper-evident trail. When auditors ask who reached a sensitive dataset — and who actually did — the answer is a query, not a quarter-long project.
How It Works

From Invisible to Governed in Four Steps

A phased approach that drops risk steadily without a big-bang migration.

🔍
Inventory
Discover and register every identity across your environment — including the shadow service accounts and unmanaged AI agents you didn't know existed. Read-only. Zero disruption.
⚖️
Govern
Apply least-privilege policies uniformly. Each identity gets exactly the access its purpose requires, with an owner accountable for it. New identities governed first, existing ones progressively enforced.
✅
Verify
Continuously authenticate and re-evaluate every identity against live signals — behavior, context, device posture — instead of trusting a login that happened hours ago.
📊
Prove
Generate audit evidence on demand — who, what, when, and under which policy — for any identity, human or machine. Compliance becomes a routine export, not a fire drill.
Use Cases

The Problems foundation.ms Was Built to Solve

AI Deployment
Deploying AI Agents Safely
Before an agent touches production systems, it is registered, scoped to a purpose, and bound to an owner. If it misbehaves, it can be suspended instantly — and every action it took is attributable. AI deployment with accountability built in, not bolted on.
Machine Identity
Taming Service Account Sprawl
Years of accumulated machine identities — many with standing privileges nobody remembers granting — are inventoried, right-sized, and put under rotation. One of the largest silent attack surfaces in the enterprise, systematically collapsed.
Compliance
Passing the Audit Without the Fire Drill
Compliance reviews that once consumed weeks of evidence-gathering become routine exports. The audit trail is generated continuously as a byproduct of normal operation — so when the request comes in, the answer is already there.
Who It's For

Built for the People Responsible for Identity at Scale

✓
CISOs Establishing an identity-first security architecture before AI adoption accelerates — and before the gaps become breaches.
✓
IAM & Security Engineering Teams Consolidating fragmented identity tooling into one governed, auditable control plane that covers all identity types.
✓
Platform Teams Who need agent governance built into the platform layer — not retrofitted project by project.
✓
Compliance & Audit Leaders Who need continuous, defensible evidence rather than a manual reconstruction every cycle.
Why Identity Is the Foundation, Not the Afterthought
Most security programs were designed for a world where identities meant people. That world is gone. AI agents and machine identities already outnumber humans in many enterprises — they operate at machine speed and often carry more privilege than any employee.

The organizations that thrive in the AI era will be the ones that treated identity as the foundation of their architecture. foundation.ms exists to make that foundation real — before the next agent deployment, not after the next breach.
"Humans, machines, and agents. One fabric. One truth."
FAQ

Common Questions

How is this different from our existing IAM stack? ▾
Traditional IAM was built around workforce identities. foundation.ms extends the same rigor — inventory, least privilege, continuous verification, audit — to machine and AI agent identities. All three populations are unified under one policy model instead of three disconnected tools. You keep existing investments and add the coverage they were never designed for.
Do AI agents really need their own identities? ▾
Yes. An agent acting under a shared or borrowed credential is unattributable by design. Giving each agent a registered identity with scoped permissions is the only way to answer who did what — and to revoke one agent without breaking ten others. As agent use scales, this distinction becomes the difference between a governed deployment and an ungoverned one.
Does this replace our existing PAM solution? ▾
It complements it. foundation.ms provides the unified identity fabric; privileged access controls like vaulting, rotation, and just-in-time checkout operate within that fabric — either through built-in capabilities or your existing PAM investment. The two work together, not against each other.
How disruptive is the adoption process? ▾
The foundation is laid in phases. Inventory first — read-only, zero disruption to existing systems. Then governance of new identities. Then progressive enforcement on existing ones. Risk drops steadily throughout, with no big-bang migration required. Each phase delivers measurable value before the next begins.

Lay the Foundation Before You Build the AI.

Every AI initiative you launch inherits the strength — or the weakness — of the identity layer beneath it. foundation.ms gives you a unified, governed, auditable identity fabric for humans, machines, and agents alike, so everything you build next stands on solid ground.