ThetaDriven
FIM-IAM
Facial Recognition for Data
Position, not proximity.
Like faces: you read the shape, not vector similarity.
We built FIM-IAM 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.
10 μs
Decision timeO(1)
Complexity∞
Scale
You recognize a face before you read the nametag.
Your brain doesn't search a database of faces. It reads the shape. Instant recognition. We do the same thing for data permissions.
Instant
You know who it is
No lookup required
→
Same principleInstant
Agent knows what it can access
No server call required
The precision?
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.
Your IAM was built for
humans clicking buttons.
AI agents move 1000x faster.
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.
What if the agent already knew?
Like you recognize a face without checking a database, what if your agent could verify permission without calling a server?
That's FIM-IAM. The agent carries a geometric identity. Permissions are checked locally in 10 microseconds instead of 400 milliseconds.
40,000x faster. No infrastructure changes.
"How can a simple grid handle enterprise scale?"
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.
Why Traditional ACLs Break
Watch the race: 40 seconds vs 10 microseconds
Traditional ACL/RBAC
O(n^2) to O(n^3) per decision
FIM-IAM Geometric
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.
While Your Agents Wait for Permission...
Your competitor with FIM-IAM is already done.
Your Current IAM (Traditional ACL)
Permission checks per agent
conservative estimate100/min
Latency per check
database round-trip400ms
Wait time per minute
67% of time waiting40 sec
Per 8-hour day
wasted on permission checks5.3 hours
With 10 agents running
53 hours/day
of cumulative agent wait timeCompetitor with FIM-IAM
Permission checks per agent
same workload100/min
Latency per check
local grid comparison10μs
Wait time per minute
0.0017% of time waiting1ms
Per 8-hour day
total permission overhead0.5 sec
With 10 agents running
5 seconds/day
of cumulative permission overheadThe Math That Matters
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.
40,000x
slower per decision
5.3 hrs
wasted per agent/day
$0
infrastructure change
We built FIM-IAM so you don't have to give competitors a 40,000x advantage. Ready to work with us?
Read the Shape at a Glance
Three grids tell the complete story: what the agent can do, what the resource requires, and whether they match.
AI Agent Capabilities
Hot = can act | Cold = blockedResource Requirements
Sparse = precise requirementsOverlay Result
Green = covered | GRANTED in 10 μsWhy This Is Different (Not Just Better)
Asymmetry IS Policy
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.
Meta-Access IS Visible
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.
Direction IS Audit
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.
Agents IS Portable
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.
The "Click" Test
Traditional IAM: Reads the Label
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.
FIM-IAM: Checks the Shape
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.
We built a physical locking mechanism for data.
The mechanical "click" is the authorization. It is binary. 1 or 0.
FIM-IAM is the geometry that makes the key turn. We want to hand you that key.
The Event Is the Pilot Program Kickoff
Why first 10? We can only do high-touch with 10 organizations. We want to work closely with early partners - iterate together, solve real problems together, and build something that works for your stack.
Why 10+ seats? If you're serious about deploying FIM-IAM, 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."
Built for Agentic Implementors
Anthropic / Claude integrators
MCP tool permissions at scaleOpenAI / GPT integrators
Function calling authorizationLangChain / LlamaIndex teams
Agent chain permission inheritanceEnterprise AI security
Replacing RBAC for AI workloadsPlatform architects
Multi-tenant agent isolationHow We Work Together:
Seats proportional to your IAM responsibility → shows us you're ready
10+ seats → we invite you to the event (first 10 orgs only)
Event → we discuss licensing together, not training
Pilot partnership → we deploy FIM-IAM with you, hands-on
We want partners who get it. Your seat count tells us you're one of them.
FIM-IAM: The 12x12 Identity Grid
Pre-license access to patent-pending methodology
PDF guide (shareable)
Interactive grid builder
Implementation docs
Licensing priority
How many seats?
x $19.99 each
1 seat x $19.99
$19.99
Enterprise licensing or 100+ seats? Contact elias@thetadriven.com
