ThetaDriven
We built IAM FIM because vector DBs find what is near. We show what is where.
12 node identities. Unlimited depth. O(1) decisions.
One geometric key for humans AND AI agents - and we want to build it with you.

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You worry about the liabilities of agentic AI
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You want to be able to say "we will do better next time" — but you felt it, the splinter in your mind
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You know we have no clue what's going on in the black box (and if you think you can see inside, that's likely... a hallucination)
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You've heard the consensus: we can't fix AI reasoning any more than we can fix a car engine with the hood welded shut
What if identity and access wasn't a policy you enforce — but a shape you recognize?
You know who it is
No lookup required
→
Same principleAgent knows what it can access
No server call required
More unique addresses than seconds since the Big Bang.
If you randomly guessed one identity per second since the universe began, you still wouldn't find it.
The paper explains how we achieve this with a 12×12 grid.

Tesseract Physics: Fire Together, Ground Together explains why S=P=H (Semantic = Physical = Hardware) is not metaphor—it's physics. Why cache misses, AI drift, and identity failures share one root cause. Why position-based verification beats probabilistic matching.
Read the book first to understand the Unity Principle. Then implement it with IAM FIM.
Theory → Implementation. Understanding → Action.
Insecure Code
The wilderness winsFunctional Only
Vibe Coding eraGrounded Certainty
Pioneer survivesVisits the frontier for the "vibe." Takes some photos. Goes home.
• Relies on luck (probability)
• Confidence scores: "80% likely"
• When the storm hits, they freeze
Goes to the frontier to build civilization. Knows entropy is trying to kill them.
• Relies on geometry (The Grid)
• Binary existence: P=1 (it IS or IS NOT)
• Laying the rails, not riding the horses
Symbol = Physics = Hardware (i.e., closer to how humans actually work)
When these three are unified, the system cannot drift. Not because it chooses not to, but because the geometry forbids the motion.
This is not a promise. This is physics.
If you're deploying AI agents, you already feel this:
Every time an agent needs to check permission, it calls a server. 400 milliseconds.
At 100 permission checks per minute, your agents spend 67% of their time waiting.
That's not a bottleneck. That's a competitive extinction event.
Like you recognize a face without checking a database, what if your agent could verify permission without calling a server?
That's IAM FIM. The agent carries a geometric identity. Permissions are checked locally in 10 microseconds instead of 400 milliseconds.
40,000x faster. No infrastructure changes.
Great question. Your bank account number is 17 digits - it doesn't contain your money. It routes to the vault.
FIM works the same way. The 12×12 grid doesn't store your permissions. It addresses them.
The result? More unique identity addresses than seconds since the Big Bang.
The paper walks through exactly how we achieve this. It's elegant once you see it.
O(n^2) to O(n^3) per decision
O(1) - Always 144 comparisons
AI agents make hundreds of permission decisions per minute. Traditional ACLs require 400ms per check. At 100 checks per minute, that is 40 seconds of waiting every minute. FIM does it in 1 millisecond total.
Permission checks per agent
conservative estimateLatency per check
database round-tripWait time per minute
67% of time waitingPer 8-hour day
wasted on permission checksWith 10 agents running
Permission checks per agent
same workloadLatency per check
local grid comparisonWait time per minute
0.0017% of time waitingPer 8-hour day
total permission overheadWith 10 agents running
Every minute your agents spend waiting for permission checks is a minute your competitor's agents are working.
At scale, this compounds. 10 agents x 5.3 hours/day = 53 hours of lost productivity daily.
That is not a rounding error. That is a competitive extinction event.
slower per decision
wasted per agent/day
infrastructure change
Three grids tell the complete story: what the agent can do, what the resource requires, and whether they match.
We encode policy in geometry: Cell(Team,Global) is not equal to Cell(Global,Team). Publishing upward requires approval authority; broadcasting downward requires delegation authority.
We separate operational access from classification authority. Writing TO a sensitivity level differs from writing AT that level. Your compliance team sees the shape, not just pass/fail.
We capture escalation vectors in the grid itself. Your auditors see the shape of the action - where permission flowed, not just whether it was granted.
We designed FIM so agents carry their grid - no server dependency. Sub-agents inherit via bitwise AND. We built the only IAM model that scales with you.
Traditional IAM reads the brand name on the key ("User: Elias"), looks it up in a book, and hopes the book is up to date.
1. Parse the label
2. Query the database
3. Traverse role hierarchy
4. Evaluate policies
5. Cross-reference tags
6. Hope nothing changed
This is probabilistic. It guesses.
When you insert a key into a deadbolt, the mechanism doesn't read the brand name. It checks the shape. If the geometry aligns, the lock turns instantly.
1. Agent carries 144-cell grid
2. Resource declares requirements
3. Single local comparison
4. Binary result: Click or no click
This is deterministic. It knows.
The mechanical "click" is the authorization. It is binary. 1 or 0.
IAM FIM is the geometry that makes the key turn. We want to hand you that key.
"The Map Controls the Territory."
When the symbol (the Code/Permission) is grounded, the Agent cannot violate physics. The Geometry forbids the motion.
Without Grounding: The Agent promises to be safe. (Vibing)
With Grounding: The Agent is physically incapable of being unsafe.
"The Territory Verifies the Map."
When physical reality changes, the Symbol updates instantly. They are the same thing.
Without Grounding: Dashboard says "All Good," engine is on fire. (Drift)
With Grounding: The symbol IS the engine state.
A train can go 300mph because it is grounded to the rails.
A car on ice (Vibing) has to go 10mph to stay alive.
Humans and bots both need a grip on reality. The book explains why. The CRM trains your reps. IAM FIM grounds your agents.
We also built the first CRM that's a flight simulator — it coaches you through the sale, not just tracks it.
Call Tia: (737) 299-7157Our AI receptionist has the full methodology in context. Try to break her.Why selective? We can't build with everyone at once. We want to work closely with qualified partners - iterate together, solve real problems together, and build something that works for your stack.
Why 10+ seats? If you're serious about deploying IAM FIM, your security architects, platform engineers, and AI leads all need to understand it. 10+ seats signals you're ready to implement with us, not just explore.
The event isn't training. It's "let's figure out together how we deploy this at your org."
How We Work Together:
Seats proportional to your IAM responsibility → shows us you're ready
10+ seats → we invite you to the event (qualified orgs only)
Event → we discuss licensing together, not training
Pilot partnership → we deploy IAM FIM with you, hands-on
We want partners who get it. Your seat count tells us you're one of them.
Pre-license access to patent-pending methodology
PDF guide (shareable)
Interactive grid builder
Implementation docs
Licensing priority
x $19.99 each
1 seat x $19.99
Want to understand WHY this works?
The book explains the physics. IAM FIM implements it.
Enterprise licensing or 100+ seats? Contact elias@thetadriven.com
IAM FIM by ThetaDriven