[IAM]

Identity and Access Management (IAM) Solution and Integration

IDENT1TY designs, integrates, and operates your identity and access management (IAM) architecture: unified governance of human, machine, and AI agent identities, with contextual access and a full audit trail. As a vendor neutral integrator, we deploy the right IAM platform inside your environment, on time and with no blind spots.

What is Identity and Access Management?

Identity and access management (IAM) is the framework of policies, processes, and technologies that ensures the right identities have the right access to the right resources, at the right time, and for the right reasons. It is the overarching discipline that manages every identity in an organization, human, machine, and increasingly AI agent, from creation to removal.

 

IAM rests on three core functions: identification (establishing who or what an identity is), authentication (proving that identity, through passwords, MFA, or passwordless methods), and authorization (granting or denying access based on roles and policies). Around these sit the broader capabilities of provisioning, single sign-on (SSO), lifecycle management, and governance.

 

IAM is the umbrella category that contains more specialized disciplines. Identity governance and administration (IGA) handles access reviews and certification, and privileged access management (PAM) secures the most sensitive accounts. A modern IAM program unifies all of these so that human users, service accounts, APIs, and AI agents are governed under one consistent, audited model rather than in disconnected silos.

 

IAM, IGA, and PAM: how they fit together

IAM is often confused with its own sub-disciplines. The clearest way to understand it is as the parent category.

IAM (identity and access management) is the whole framework: it decides who can sign in, with what credential, to which resource, across the entire identity population.

 

IGA (identity governance and administration) is the governance layer inside IAM. It answers whether the access an identity already holds is still appropriate: who reviewed it, when it expires, and how it is deprovisioned.

 

PAM (privileged access management) is the layer inside IAM that secures the most powerful accounts, administrators, root, and service accounts, with vaulting, session recording, and just-in-time access.

 

In short: IAM governs all access, IGA governs whether that access stays appropriate, and PAM protects the privileged few. A mature identity program deploys all three as one connected architecture, which is exactly where integration expertise matters most.

Why choose an IAM integrator over a single vendor

Most IAM vendors sell you a platform. But IAM environments are more exposed than teams think, not because the software is weak, but because access rights go uncontrolled, projects stall halfway, and undersized teams cannot operate the tooling they bought.

 

As a vendor neutral integrator, IDENT1TY delivers the part that determines success. We unify human, machine, and AI agent identities into one audited governance model, integrate the right platform across your directories and applications, and operate it so access stays controlled and adaptive over time.

 

That means you get:

  • A single repository for all identities, employees, contractors, AI agents, and applications, with no invisible drift.
  • Contextual, adaptive access that adjusts to risk, device, and business context, without friction for legitimate users.
  • A full, exploitable audit trail across Active Directory, Entra ID, Okta, and cloud, so security and compliance teams save hours on every investigation.

 

A pure vendor optimizes for its license. An integrator optimizes for access you control and can prove, from day one.

Why most IAM environments are more exposed than you think?

Uncontrolled access rights

Exposure to cyber threats, non-compliance NIS2/ISO27001

Abandoned projects halfway

Increased costs, results never achieved

Undersized teams

Delays, publisher dependence, operational risks

A centralised, audited access management with no blind spots

Traditional IAM manages users in silos. IDENT1TY unifies human, machine and application identities in consistent, real-time audited governance.

Unified human + machine view

A single repository for all identities: employees, contractors, AI agents, applications. No more invisible drift.

Contextual and adaptive access

Rights automatically adjust based on risk profile, device and business context, without friction for legitimate users.

Full and exploitable audit trail

Every action is logged, correlated and exportable. Security and compliance teams save hours on every investigation.

Seamless integration into your IT landscape

Native connectors with Active Directory, Entra ID, Okta, Google Workspace. Deployed in weeks, not months.

What we do today

We help organizations identify, classify and govern AI agents as fully fledged digital identities in their own right.

Mapping · Governance · IAM · IGA
01
Mapping and governance model
  • Mapping of the AI agents used across the organization, including official, experimental and undeclared agents
  • Definition of a governance model specifying the owner, scope, risk level and purpose of each agent
02
Lifecycle rules and alignment
  • Implementation of rules for the creation, validation, modification and decommissioning of identities associated with AI agents
  • Alignment of AI agent governance with existing IAM, IGA, PAM, cloud security and machine identity policies

We secure the access granted to AI agents in order to limit excessive privileges and the risk of unauthorized actions.

Least privilege · Permissions · Zero Trust
01
Access models and granular permissions
  • Definition of access models based on the principle of least privilege, context, agent role and the criticality of actions
  • Implementation of granular permissions across applications, APIs, data, internal tools and cloud environments
02
Control of sensitive actions
  • Framing of sensitive actions through human approval, just-in-time access and conditional rules
  • Reduction of the risk of privilege escalation, lateral movement or indirect access through agent chains

We protect the secrets used by AI agents to prevent leaks and invisible dependencies on credentials.

API Keys · OAuth · Rotation · Vaulting
01
Vaulting and rotation policies
  • Secure vaulting of API keys, OAuth tokens, certificates, service accounts and secrets used by AI agents
  • Implementation of rotation, expiration, revocation and scope-limitation policies for credentials
02
Elimination of exposed secrets
  • Removal of secrets exposed in prompts, memories, logs, configuration files or code repositories
  • Strict separation of credentials by agent, environment, application, risk level and business use

We enable organizations to know exactly what an AI agent has done, with which privileges and on which data.

Logging · SIEM · Audit · Accountability
01
Logging and correlation
  • Comprehensive logging of the actions performed by AI agents: access, requests, API calls, changes, decisions and executions
  • Correlation of AI events with existing SIEM, SOC, ITSM, PAM, IAM and monitoring platforms
02
Detection and audit evidence
  • Implementation of detective controls for abnormal behavior, destructive actions or unauthorized access
  • Production of audit evidence that traces accountability across the user, the agent, the tool and the action performed

We help our clients secure the chains of autonomous actions executed by AI agents.

Human-in-the-loop · Guardrails · Agentic AI
01
Analysis and guardrails
  • Analysis of agentic workflows to identify decision points, sensitive actions and critical dependencies
  • Implementation of guardrails for high-impact actions: deletion, configuration changes, access to production
02
Tool control and human validation
  • Control of the tools accessible to AI agents in order to limit unnecessary or dangerous capabilities
  • Definition of human-in-the-loop scenarios to enforce human validation before critical operations

We support organizations in establishing a measurable control framework to secure the use of AI agents.

NIST AI RMF · EU AI Act · Audit · Risk
01
Risk assessment and internal policies
  • Assessment of the risks associated with AI agents according to use cases, the data handled, the systems accessed and the level of autonomy
  • Definition of internal policies governing the use, access, responsibilities and operational limits of AI agents
02
Dashboards and regulatory alignment
  • Implementation of compliance dashboards covering agents, their privileges, their actions, their exceptions and their incidents
  • Alignment of controls with AI security and risk-management frameworks, notably NIST AI RMF-style approaches

Our numbers talk for us

28

years of experience

+100

Active Certifications

76

Projects deployed in 2025

17

Countries covered

+40

IAM/PAM/IGA certified experts

Use cases

AI AgentsUniversal bank

AI agent supporting the identity service desk

Automated handling of level-1 access requests under human supervision, with compliance guardrails.

6 months
6,000 requests / month
ITSM · IGA · AI · DORA

The identity service desk was handling a high volume of repetitive requests, leaving the IAM teams little time for higher-value work.

The security leadership wanted to trial an AI agent capable of absorbing level-1 requests, without degrading compliance or replacing human oversight on sensitive decisions.

Value-adding work constantly pushed back by the flow of repetitive tickets
Multi-hour SLAs on trivial requests, a major source of user frustration
ACPR and DORA compliance risk tied to automation without a governed framework
Need to preserve human oversight on sensitive decisions and cryptographic governance
01Mapping of automatable level-1 requests and definition of compliance guardrails
02Design of an AI agent with automatic escalation to a human operator for sensitive or ambiguous cases
03Integration into the existing ITSM with full logging of every decision for audit purposes
04Implementation of a documented AI governance framework aligned with DORA and ACPR requirements
05Pilot phase on 20% of requests with progressive validation before full rollout
65% of level-1 requests handled automatically without human intervention
Average SLA reduced from 4 hours to 15 minutes on automated requests
100% of decisions auditable with full traceability of the accountability chain
IAM teams freed up to focus on high-value projects
AI governance framework validated by the compliance teams and presented to the regulator
65%
Level-1 requests automated
4h → 15min
Average user SLA
100%
Auditable decisions

Another use case, another challenge.

AI AgentsInsurance – mutual group

AI agent supporting access review decisions

Contextual recommendations and risk scoring to turn IGA campaigns into qualitative reviews.

5 months
9,000 employees · 250 applications
IGA · AI · Scoring · Compliance

Access review campaigns suffered from mass, undifferentiated rubber-stamping. Managers, faced with hundreds of accesses to validate, were approving without any real analysis.

The goal was to bring meaning back to the reviews without adding to the managers' workload, by leveraging available data to focus their attention on genuinely high-risk access.

Managers with neither the time nor the context to analyze each entitlement individually
Usage logs, entitlement age, peer comparisons — signals available but unexploited
Strong requirement for explainability towards internal control
Not to impose an automatic decision but to help managers decide better
01Development of a scoring engine leveraging usage logs, entitlement age and peer comparisons
02Integration of the recommendations directly into the existing IGA review interface, without changing the tool
03Each recommendation paired with an explanation readable by the manager and traceable for audit
04The manager remains the decision-maker: the agent proposes, the human validates or overrides. Progressive model learning from the decisions validated by managers
45% increase in high-risk entitlements correctly revoked from the very first campaign using the scoring
40% reduction in manager time per review campaign thanks to contextual recommendations
100% of recommendations explainable and traceable, validated by internal control
Campaign completion rate raised from 68% to 94% thanks to the simplified interface
Continuously improving model, with recommendation accuracy rising with each campaign
+ 45%
High-risk entitlements revoked
− 40%
Manager time per review
100%
Explainable recommendations

How Ident1ty works on your project IAM

Solution
integrator

We deploy your IAM solution from A to Z

Continuous Support & Managed Services

We maintain and optimize your IAM environment

Success
Plan

A dedicated CSM to support you.

Consulting &
Expertise

Certified experts to frame your identity strategy.

Our technology partners

FAQ

Identity and Access Management FAQ

Clear answers on what IAM is, how it relates to IGA and PAM, and what a modern identity program covers.

If human, machine, and AI agent identities live in separate silos, these are the questions worth asking now.

What is identity and access management?
Identity and access management (IAM) is the framework of policies and technologies that ensures the right identities have the right access to the right resources, at the right time. It covers identification, authentication, and authorization for human, machine, and AI agent identities.
What are the main components of IAM?
IAM rests on three core functions: identification (who an identity is), authentication (proving it, through passwords, MFA, or passwordless methods), and authorization (granting access based on roles and policies). Around these sit provisioning, single sign-on, lifecycle management, and governance.
What is the difference between IAM and IGA?
IAM is the overarching framework that manages all identities and their access. IGA (identity governance and administration) is the governance layer inside IAM that reviews and certifies whether the access an identity already holds is still appropriate over time.
What is the difference between IAM and PAM?
IAM governs access for the whole identity population. PAM (privileged access management) is the layer inside IAM that specifically secures the most powerful accounts, such as administrators and service accounts, with vaulting, session recording, and just-in-time access.
What is the difference between authentication and authorization?
Authentication proves who a user or machine is, for example through a password, MFA, or passkey. Authorization then decides what that verified identity is allowed to access. IAM handles both, in sequence, at the moment of access.
Does IAM cover machine and AI agent identities?
Yes, and increasingly it must. Non-human identities such as service accounts, APIs, and AI agents now outnumber human users by a wide margin. A modern IAM program governs them under the same audited model as human identities, with clear ownership and lifecycle control.

Your IAM project deserves support from certified specialists.

30 minutes with our consultants to evaluate your project, free and without commitment.

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