The Frontier Firm era has begun
What enterprises build in 18 months, we create in days.
Fortune 500 companies spend millions building AI-ready data infrastructure. They have to - their data lives in legacy systems that require manual integration. But if your business runs on modern SaaS, that infrastructure can be generated automatically.
First outcome in minutes, not months
No data engineering team required
Works with your existing SaaS stack
The Enterprise Approach
Why enterprise AI infrastructure takes 18 months and $1M+
The traditional path to production AI - whether through Palantir, custom builds, or big-firm implementations - follows a well-worn playbook:
The timeline isn't about technology - it's about data reality.
Enterprise data is messy. It lives in legacy ERPs, on-prem databases, custom systems built over decades. The semantic meaning - what a "customer" or "order" actually represents in this business - isn't explicit. It has to be extracted, modeled, and maintained by humans.
This is necessary work. For companies with decades of legacy infrastructure, there's no shortcut. The data has to be unified before AI can understand it.
But what if your data isn't messy?
What if your business runs on modern SaaS systems that already structure data correctly?
What if the ontology is already implicit in how your systems work?
A Different Way In
Your SaaS stack already generates everything AI needs. You're just not capturing it.
Here's what enterprises spend 18 months building:
A unified data layer connecting all their systems
A business ontology that AI can reason over
Schema governance ensuring consistent meaning
Real-time context for grounded AI decisions
95% of AI pilots fail to reach production (MIT 2025) - primarily due to lack of structured business context
They build this manually because their data lives in legacy systems - ERPs from the 90s, on-prem databases, custom integrations accumulated over decades. The data exists, but it's scattered and unstructured.
Your situation is different.
If your business runs on Salesforce, HubSpot, Zendesk, NetSuite, Stripe - modern SaaS systems - you're already generating structured, meaningful business events.
Every deal stage change. Every support ticket escalation. Every invoice payment.
These aren't just data points. They're semantic events with entities, relationships, and business context embedded in them.
What
Actually Does
1
Connects to your SaaS systems
Native integrations, not ETL pipelines. Real-time event capture, not batch processing.
2
Generates semantic events automatically
Native integrations, not ETL pipelines. Real-time event capture, not batch processing.
3
Builds your
Business Ontology
Native integrations, not ETL pipelines. Real-time event capture, not batch processing.
4
Governs through the
Event Bible
Schema-level governance embedded in the architecture. Not a policy layer added on top.
The Result
The same infrastructure that Fortune 500 companies build with data engineering teams and 18-month timelines — generated automatically from your existing SaaS stack.
Approach
Setup Time
Accuracy
Ontology Type
Manual Engineering
12–18 months
~95%
Static (batch-based)
Vector RAG
Minutes
~0%
None
FaiOS
Days
>90%
Active (event-driven)
Not a shortcut. Not a "lite" version. A fundamentally different path that's only possible because modern SaaS-native businesses generate structured data by default.
Works With What You Have
If it's in your stack,
it's in your ontology.
FraiOS connects to the SaaS systems you already use.
Every event from these systems becomes part of your Business Ontology - automatically.
But we go further
With a security model designed for the AI era. Enterprise identity management via WorkOS integrates seamlessly with your existing Okta, Entra, or Google Workspace SSO — every agent inherits your existing security model from day one.
Sales
Opperations
Support
Finance
New connectors added regularly. Custom integrations available for enterprise.
Each of these systems already generates structured, meaningful events. FraiOS captures them, enriches them with entity relationships, and weaves them into your Business Ontology.
No ETL. No data engineering. Just connection and capture.
Control Without Compromise
Enterprise-grade control.
A fundamentally different security model.
The industry learned that control matters as much as intelligence for production AI. We agree completely. That's why FraiOS was built with governance embedded at the architectural level - not added as a policy layer.
Ephemeral by Design
Traditional AI systems accumulate context over time - creating expanding attack surfaces and compliance risks. FraiOS inverts this.
Every AI agent session is stateless. Data access is granted per-task, not persistent. When the task ends, the context disappears. This isn't a limitation - it's a security primitive.
What this means
They build this manually because their data lives in legacy systems - ERPs from the 90s, on-prem databases, custom integrations accumulated over decades. The data exists, but it's scattered and unstructured.
No accumulated context to breach
No persistent data exposure from AI systems
Automatic data minimization by design
Per-task access scoping that matches your governance requirements
Full Observability.
Zero Exposure.
"But wait - if data disappears, how do you maintain audit trails?"
Through semantic logging. FraiOS captures complete audit trails at the meaning layer - what happened, who did it, what entities were involved, what the outcome was - without persisting the underlying data payloads.
Your compliance team gets 100% visibility. Your security team gets zero data residue.
Is This You?
Built for SaaS Era companies on the journey to becoming Frontier Firms
The industry learned that control matters as much as intelligence for production AI. We agree completely. That's why FraiOS was built with governance embedded at the architectural level. But we go further with a security model designed for the AI era.
You're a FraiOS fit if:
Your stack is modern
• 50-200 SaaS applications running your business
• Salesforce, HubSpot, Zendesk, NetSuite, Stripe, Slack — the tools that matter
• No legacy ERP from 1997. No on-prem databases you're afraid to touch.
Your team is lean
• 100-2,000 employees
• No dedicated data engineering team (or maybe 1-2 people doing everything)
• IT focused on operations, not building custom infrastructure
Your ambition is enterprise-grade
• You've seen what AI can do for Fortune 500 companies
• You want that capability — the operational intelligence, the autonomous agents, the real-time visibility
• You just don't have 18 months and $1M to get there
The Growth-Stage Company
$50M-$500M revenue. Growing fast. Running entirely on SaaS. You know AI could transform your operations, but every "enterprise AI" conversation ends with a timeline and budget that doesn't fit your reality.
The Ambitious Operations Leader
VP of Ops, RevOps, or Business Operations. You see the inefficiency everywhere. You know what questions you'd ask if you had the data. You're tired of waiting for IT to build dashboards.
The "We Should Be Further Along" Company
You've tried AI tools. Chatbots, copilots, point solutions. They help, but they don't transform. They don't understand your business. You know there's a better way — you just haven't found it.
Your Dedicated Team
FraiOS gives every employee their own dedicated team of AI agents.
Not coding. Not configuring complex systems. Describing what they need and deploying agents to handle it.
This is what enterprise AI infrastructure enables. FraiOS makes it accessible to companies who don't have Fortune 500 resources - because you don't need Fortune 500 resources if your data is already structured.
Fortune 500 companies spend $1M+ building this infrastructure.
You could have it by end of day.
Your SaaS stack already generates everything AI needs to understand your business. FraiOS captures it automatically - no data lake, no engineering team, no 18-month timeline.
No credit card required
Works with your existing SaaS stack
First results in days, not months