The "Long Tail" of Identity: Why Your GRC Platform Needs Coverage Beyond the Top 5 IdPs

Most GRC (Governance, Risk, and Compliance) platforms proudly display their integration pages featuring Okta, Microsoft Entra ID, Google Workspace, and Ping Identity. Engineering teams build these core connectors, check the identity management box, and move on to the next roadmap item.

But enterprise identity doesn't stop at the top five Identity Providers (IdPs).

Underneath the surface of standardized Single Sign-On (SSO) lies a massive, fragmented "long tail" of identity. This includes localized Active Directory deployments, legacy on-premise systems, niche IdPs like JumpCloud or ForgeRock, and HRIS platforms (like BambooHR) functioning as the actual source of truth.

If your GRC platform cannot automatically pull user access data from this long tail, your customers are stuck doing manual CSV exports to complete their User Access Reviews (UARs). An incomplete identity graph isn't just an inconvenience—it's a direct path to SOC 2, SOX, and ISO 27001 audit failures.

The 32% Blind Spot in User Access Reviews

When an auditor asks for proof of access controls or segregation of duties (SoD), they don't just want data from Okta. They demand proof across the entire organization, including contractors, shadow IT, and legacy subsidiaries.

Recent industry analyses indicate that roughly 32% of enterprise applications and identity data remain disconnected from centralized identity platforms. Instead, they rely on manual CSV uploads, fragmented SQL queries, or ad-hoc Python scripts.

If a customer buys your GRC tool to automate compliance, but still has to manually map identity data for a third of their infrastructure, your product has failed its primary objective.

Why Integrating the Long Tail is an Engineering Nightmare

Building integrations for the top IdPs is relatively straightforward. They have well-documented APIs, predictable rate limits, and massive developer communities. The long tail is an entirely different beast.

The SCIM Protocol Illusion

System for Cross-domain Identity Management (SCIM) 2.0 was supposed to standardize identity integrations across the industry. In reality, SCIM implementations are wildly inconsistent, and treating SCIM as a universal plug-and-play standard will break your application.

Vendors routinely deviate from RFC 7643 and 7644. For example, AWS IAM Identity Center's SCIM implementation only supports the exact match (eq) operator for filtering and completely drops support for multi-valued user attributes. Other platforms simply drop nested group data over SCIM, destroying your ability to accurately map inherited permissions for an access review.

When you build a "standard" SCIM connector, you inevitably end up writing dozens of custom conditional blocks to handle the quirks of specific vendors.

HRIS as the True Source of Truth

In many mid-market and enterprise companies, the IdP is just a downstream consumer of data. The HRIS (Human Resources Information System) dictates identity. When a contractor is terminated in BambooHR, that event needs to trigger compliance checks and access revocations in your GRC platform immediately.

Integrating with 40 different HRIS APIs means dealing with 40 different ways of representing an "Employee", "Contractor", or "Department". You aren't just mapping fields; you are reverse-engineering business logic to figure out if a user is actually active.

Pagination, Rate Limits, and Undocumented Edge Cases

Legacy identity systems often use archaic data retrieval methods. You will encounter offset-based pagination that times out on large datasets, XML tokens, or SOAP endpoints wrapped in poorly constructed REST facades.

Worse, many of these niche systems lack webhooks. You expect real-time event streams for user de-provisioning. Instead, you get a system that requires aggressive polling. Polling 50 different legacy APIs for state changes eats up your compute resources, triggers HTTP 429 Too Many Requests errors, and forces you to build complex backoff-and-retry queues.

The Architectural Trade-offs of In-House Integrations

When building these integrations in-house, your engineering team faces a brutal set of choices, none of which are ideal.

1. Build a custom connector for every customer request: This drains engineering velocity. You end up maintaining a graveyard of brittle, single-use API clients that break every time a vendor updates their undocumented endpoints.
2. Force customers to use Zapier or custom scripts: This pushes the engineering burden onto the customer. It leads to high churn, terrible user experiences, and a massive loss of control over data security—a massive red flag for a GRC product.
3. Rely on CSV uploads: The ultimate admission of defeat for an automated compliance platform.

Let's look at a typical problem: normalizing a user's status across different APIs to determine if they should be included in an active User Access Review.

// The nightmare of normalizing user status across APIs in-house
 
function isUserActive(user, provider) {
  switch(provider) {
    case 'okta':
      return user.status === 'PROVISIONED' || user.status === 'ACTIVE';
    case 'bamboohr':
      return user.status === 'Active';
    case 'legacy_system_x':
      // Legacy system uses integer flags and nullable deletion dates
      return user.isActive === 1 && user.deletedAt === null;
    case 'aws_iam':
      return user.active === true;
    default:
      throw new Error('Unsupported identity provider');
  }
}

Multiply this logic by 50 platforms. Add error handling, retry logic, and OAuth token refresh management. Suddenly, your core product team is spending 60% of their sprints maintaining integrations instead of building the risk scoring algorithms and audit dashboards your customers actually pay for.

Normalizing the Chaos with a Unified API

This architectural bottleneck is exactly why engineering leaders are shifting toward Unified APIs. Instead of building and maintaining dozens of distinct identity and HRIS connectors, you integrate once against a single, normalized schema.

Truto sits between your GRC platform and the long tail of identity providers. We handle the undocumented edge cases, the weird pagination schemas, the SCIM deviations, and the OAuth dances.

When you use Truto, fetching active users looks exactly the same regardless of whether the underlying system is Azure AD, JumpCloud, or a niche HRIS. We abstract away the underlying API complexity and return a clean, predictable JSON object.

// Fetching users via Truto's Unified API
const response = await fetch('https://api.truto.one/unified/users?status=active', {
  headers: {
    'Authorization': `Bearer ${TRUTO_API_KEY}`,
    'x-truto-account-id': customerAccountId
  }
});
 
const users = await response.json();
// 'users' is always a standardized array, 
// regardless of the underlying IdP or HRIS.

By abstracting the integration layer, you achieve three immediate benefits:

• Instant expansion of your Total Addressable Market (TAM): You can now confidently sell to enterprises using legacy or niche identity stacks, knowing you can support their infrastructure out of the box.
• Reclaimed engineering focus: Your team stops writing API wrappers and goes back to building core GRC features.
• Reliable, automated UARs: 100% automated data ingestion means your customers actually pass their audits without resorting to spreadsheets.

The Strategic Cost of Ignoring the Long Tail

Compliance is binary. You either have complete visibility into who has access to what, or you don't.

If your GRC platform only covers the top 5 IdPs, you are forcing your customers to manually bridge the gap for the remaining 32% of their infrastructure. They will eventually migrate to a competitor that offers complete, automated coverage.

Stop wasting engineering cycles on brittle API connectors. Standardize your integration layer, cover the long tail, and give your customers the automated compliance they actually paid for.