Why We Switched From WorkOS to SSOJet for Enterprise SSO (and Saved $5,000 a Year)

GrackerAI paid WorkOS $625 a month for five enterprise SSO (Single Sign-On) connections. We now pay SSOJet about $208 a month for the same five connections, plus the flexibility to build custom AI-agent authentication flows that WorkOS's framework wasn't designed to accommodate. The switch happened in 2025. It saves us roughly $5,000 a year, and the money was the smaller reason we made the move.

GrackerAI is my company, a generative engine optimization (GEO) platform that helps B2B SaaS and cybersecurity companies get cited by ChatGPT, Perplexity, and Google AI Overviews. We ran on WorkOS for several months, handling SSO for our first five enterprise customers, before an architecture review surfaced a question that mattered more than the invoice. Our engineering lead asked it directly: are we building authentication the right way for a platform whose product is AI agents acting on behalf of users?

That question, not the cost difference, is what moved us. The savings just made the decision easier to justify.

Why WorkOS Is a Good Platform, Just Not for Us

WorkOS is a genuinely good product, and I want to say that plainly before explaining why we left. The developer experience is strong. We integrated our first SSO connection in under a week. Documentation is thorough. The Admin Portal gives customer IT teams real self-service instead of a support ticket queue. The platform has been reliable every time we've used it.

Pricing is transparent: $125 per connection a month, with volume discounts at scale, no hidden fees. Support has been responsive every time we asked a question during implementation.

For most B2B SaaS companies, that combination is the right answer. If you need enterprise SSO fast, want minimal engineering investment, and your authentication requirements fit standard patterns, WorkOS delivers real value for the price.

GrackerAI's authentication requirements don't fit standard patterns. We needed deeper control over how SSO integrates with AI agent workflows: custom token flows, extended session lifetimes for long-running AI tasks, delegated access where an agent acts on a user's behalf. WorkOS handles conventional enterprise SSO well. Conventional wasn't what we needed.

Why AI Platforms Need Protocol-Level Control

Traditional SaaS can tolerate some authentication vendor lock-in. A CRM or project management tool can switch identity providers without touching its core product, because the product doesn't depend on authentication architecture. Inconvenient, not existential.

AI platforms don't get that luxury. They authenticate both humans and machine agents. They handle delegation, where an AI agent acts on a user's behalf inside another system. They need flexible token lifetimes for AI tasks that run for minutes or hours, not the seconds a typical API call takes. And the standards for how any of this should work are still being written. Locking your implementation into one vendor's proprietary layer on top of those standards means you can't adapt as the standards themselves change, and in 2026 they're changing quickly. I go through the category boundaries in more detail in my CIAM vs IAM vs IDaaS guide, worth reading before you pick a vendor category, not after.

OIDC (OpenID Connect) and SAML (Security Assertion Markup Language) aren't just protocols here. They're insurance. Building on them means your authentication can evolve as your AI platform evolves, independent of any single vendor's roadmap.

Both WorkOS and SSOJet support these standards. The difference is architectural philosophy. WorkOS gives you a complete authentication solution built on standards and handles the complexity for you. That's valuable, but you work within their implementation patterns. SSOJet gives you standards-based building blocks and lets you assemble the implementation yourself. You own the details while staying protocol-compliant.

When we built AI agent authentication into GrackerAI, we needed token flows that extended standard OIDC patterns without breaking them. SSOJet's approach let us do that while staying fully protocol-compliant. We weren't requesting custom features from a vendor or working around a platform's constraints. We were building the way modern API authorization for AI agents actually works: OAuth 2.1 (the IETF draft succeeding OAuth 2.0), scoped tokens, and either Authorization Code or CIBA flows to capture explicit user consent before an agent acts. CIBA stands for Client-Initiated Backchannel Authentication, the OpenID flow built for exactly this kind of consent step.

What Custom Implementation Actually Bought Us

The biggest surprise after switching wasn't the savings. It was how much friction disappeared from custom implementation work.

Inside WorkOS's framework, deviating from standard patterns meant fighting the framework. Custom attribute mapping for AI agent contexts required workarounds. Extended token lifetimes for long-running AI tasks needed configuration that pushed against platform boundaries. Delegated flows, where an agent acts on a user's behalf, were possible but architecturally awkward. None of that is a WorkOS flaw. It's what happens inside any complete framework: making the common case easy means constraining the uncommon case.

SSOJet doesn't provide a complete framework. It provides standards-based components you assemble yourself. That let us:

• Build AI agent authentication for our own workflows. Fine-grained delegation controls and audit trails for agents requesting access to user data, fully OIDC-compliant, implemented for our specific use cases rather than a generic template.
• Set token lifetimes that match AI execution patterns. Long-running analysis tasks need refresh patterns that balance session length against security, not the short-lived tokens built for a typical browser session.
• Build custom IdP (Identity Provider) integrations for security-conscious enterprise customers. Some of the cybersecurity companies we serve have specific requirements around how AI systems access their environment. We could accommodate those without waiting on a platform roadmap.

A platform with a hundred features you can't customize is worth less than a platform with twenty you can implement exactly right. That's the tradeoff that mattered for us.

The Real Cost of Enterprise SSO

Here's the arithmetic, not rounded for effect.

That's just over $5,000 a year in direct connection-fee savings alone, and the total value is higher once you count the engineering hours we stopped spending working around platform constraints. But the sticker price isn't the real comparison. The question isn't which vendor is cheaper. It's which one lets us build the right architecture for an AI platform without fighting the tool to get there.

WorkOS at $7,500 a year would be a good deal if its architecture matched our needs exactly. It didn't, and the true cost of that mismatch shows up as engineering time and delayed AI feature work, not on the invoice. For five enterprise customers, that gap is manageable. At fifty, it compounds into something much larger. Architecture decisions made early don't stay small.

What to Look for in an SSO Partner for an AI Platform

A year and a half into running SSOJet in production, here's what I'd tell another AI-platform founder to check before signing anything.

• Standards compliance, verified, not claimed. Your authentication needs to be built on OIDC, SAML, and related protocols, not merely compatible with them. Ask the vendor to show you the token flows, not the marketing page.
• Room for AI-specific patterns. Agent authentication, delegated access, and extended token lifetimes for long-running tasks aren't edge cases for an AI platform. They're core requirements. Confirm your vendor supports them natively or gives you room to implement them yourself.
• Pricing that fits your growth curve. Per-connection pricing suits some businesses. If enterprise adoption is lumpy or experimental for you, flat-tier pricing is more predictable. Pick the model that matches your actual economics, not the one that sounds cheaper on a slide.
• Implementation support over feature count. A long feature list you can't customize is worth less than a shorter one you can implement correctly. Look for a partner who understands your architecture, not just a vendor with a longer comparison chart.
• Protocol ownership. Your authentication architecture will outlive any single vendor relationship. Standards-based implementation means you can switch providers later without rebuilding, which is insurance against both the vendor's decisions and your own evolving requirements.

The Bottom Line: Build on Standards, Own Your Implementation

I don't regret starting on WorkOS. For launching GrackerAI's enterprise tier, fast implementation and reliable infrastructure let us prove enterprise demand before we knew exactly what our authentication architecture needed to look like.

Once we knew, we needed more control while staying standards-compliant, and that's what switching to SSOJet gave us. We save roughly $5,000 a year in direct fees, more once engineering time is counted. More importantly, we can build enterprise SSO exactly how an AI platform needs it, on protocols that don't lock us into any one vendor's roadmap, including SSOJet's.

WorkOS is the right call for a company that wants complete, well-structured SSO with minimal engineering investment. SSOJet is the right call for a team that needs custom implementation flexibility while staying protocol-compliant. Make that call based on your own requirements, covered in my founder's guide to authentication vs authorization, not on which vendor has the better landing page.

Whatever you choose, build on standards. AI authentication is moving fast enough right now that you'll need the flexibility to move with it.

Frequently Asked Questions

Is WorkOS a good choice for enterprise SSO?

For most B2B SaaS companies, yes. WorkOS offers fast implementation, thorough documentation, transparent per-connection pricing, and a self-service Admin Portal for customer IT teams. It's the right choice when your authentication requirements fit standard patterns and you want to minimize engineering investment.

How much cheaper is SSOJet than WorkOS?

For GrackerAI's five enterprise SSO connections, WorkOS cost $625 a month ($7,500 a year) at its $125-per-connection pricing. SSOJet's current five-connection tier costs $208 a month (about $2,500 a year), a direct savings of roughly $5,000 a year before engineering time is factored in. Pricing and connection counts will differ for other companies; run your own numbers before assuming the ratio holds.

Do AI platforms need different SSO architecture than typical SaaS?

Often, yes. AI platforms authenticate both humans and machine agents, need delegated-access flows where an agent acts on a user's behalf, and require token lifetimes suited to long-running AI tasks rather than short browser sessions. A complete, framework-driven SSO platform can make these patterns harder to implement than a standards-based, component-level approach.