Oleria's Graph-Driven Approach Unifies Identity Data to Expose the Dormant Access That Fuels Modern Breaches

The modern enterprise is an identity archipelago. Human users, machine service accounts, and emerging AI agents reside across dozens of separate systems: identity providers (IdPs) like Okta, cloud platforms like AWS, SaaS applications like Salesforce, and legacy HR databases. Each system maintains its own incomplete record of who has access to what. The result is a catastrophic visibility gap. Security teams can see static permissions in individual silos but cannot answer the critical questions: Which of these millions of entitlements are actually being used? Which dormant service account holds keys to the crown jewels? This fragmented reality forces organizations into a perpetual cycle of "check-the-box" access reviews and reactive clean-up, leaving toxic, unused permissions the primary fuel for ransomware and data exfiltration persistently undiscovered.

Oleria is engineered to solve this foundational data problem. The company's core innovation is the Oleria Access Graph, a graph-native architecture that unifies, normalizes, and enriches identity data from across an organization's entire technology ecosystem. Oleria's pre-built connectors pull information not just from IdPs and directories, but from resource-level systems like GitHub, Snowflake, and Google Drive, capturing fine-grained usage activity alongside static permissions. This data is normalized into a single, common schema, creating a living map of every identity human, non-human, and AI and its actual access patterns. This transforms identity security from a compliance exercise into a continuous, data-driven risk management function.

The company’s platform, Trustfusion, leverages this unified data layer to power three core functions: continuous posture management to discover over-provisioned and dormant accounts; intelligent governance to automate access reviews with usage context; and accelerated incident response to trace compromised access paths. For security leaders, Oleria’s promise is operational clarity: the ability to see, in a single pane, which accounts are unused, where external access is over-permissive, and which identities have weak authentication and to act on those insights with automated, reversible remediation workflows, often within an hour of deployment.

The Data-First Platform Revenue Model

Oleria’s commercial strategy is built on a scalable, consumption-based platform model. Rather than selling point solutions for access reviews or posture management, it offers its Trustfusion platform as a unified system of intelligence. Revenue is generated through platform subscriptions, typically based on the volume of identities and applications connected. This model aligns Oleria’s success with the scale and complexity of the customer’s environment, creating a natural revenue expansion path as clients connect more systems and identities. The platform’s rapid deployment claims of actionable insights within an hour reduces the traditional sales friction and lengthy implementation cycles of legacy Identity Governance and Administration (IGA) suites, accelerating time-to-value and improving sales velocity.

Monetizing the Unification of Silos

Oleria’s primary value proposition is the elimination of costly integration work and tool sprawl. Enterprises often spend millions annually on IGA software, Cloud Infrastructure Entitlement Management (CIEM) tools, and manual consulting services to stitch together a partial view of identity risk. Oleria’s platform, with its pre-built connectors and common schema, is positioned as a consolidation engine. For the customer, this translates into direct cost savings on multiple tool licenses and integration projects. For Oleria, it allows the company to command a premium as a centralizing force, displacing budget from several legacy vendors and capturing the value of providing a single source of truth. This "unification fee" is justified by the dramatic reduction in manual effort and the de-risking of the entire identity attack surface.

The AI-Enabled Efficiency Engine

A key differentiator is Oleria’s focus on usage-aware intelligence, powered by domain-specific AI models. While many vendors add generative AI chatbots as a feature, Oleria’s AI is designed to continuously analyze the rich activity data in its graph to detect anomalies, dormant accounts, and privilege creep. This capability directly addresses the operational burden that drives security team burnout. By automating the analysis of millions of permission-usage pairs and prioritizing risks, the platform claims to free up significant analyst time. This efficiency gain is a powerful part of the ROI calculation, allowing Oleria to price its platform not just as a security control, but as a force multiplier for understaffed security operations, justifying its cost through measurable labor savings and risk reduction.

The Strategic Position for the AI Agent Era

Perhaps Oleria’s most forward-looking commercial bet is its architecture’s inherent suitability for securing non-human and AI identities. As enterprises deploy AI copilots and autonomous agents, these new identity types will inherit all existing over-permissions and create novel access paths. Oleria’s graph, which already maps service accounts and their usage, is designed to extend natively to these AI agents, tracking what data they access and how. This positions the company ahead of a coming wave of regulatory and security demand. By building the foundational data model now, Oleria is not just solving today’s IAM problems but is selling what is effectively future-proof infrastructure for an AI-driven enterprise, creating a long-term competitive moat and a pipeline for next-generation product modules.

The trajectory of cyber-attacks is unequivocal: identity is the new perimeter, and over-permissioned, unused access is the primary vulnerability. Security programs that remain reliant on siloed tools and manual processes are building on a foundation of sand. Oleria’s thesis is that the only viable defense is a unified, data-centric understanding of identity behavior across the entire digital estate. Its success hinges on proving that its graph-driven platform can not only illuminate today’s hidden risks with unprecedented speed but can also evolve into the central nervous system for identity security in an increasingly autonomous and AI-augmented world, where understanding access is inseparable from understanding intent.

Jim Alkove, Chief Executive Officer & Co-founder

“We built the system we always needed but never had one that shows you not just who can access your critical data, but who actually is, and what they're doing with it.”