Predictable cost
No surprise AI bills
Every agent runs inside a hard budget with early-warning signals. Finance sees the ceiling before work starts.
Governed agents
Give AI autonomy.
Without betting the company.
Real agents that act on their own, bounded by budget, gated by humans on high-stakes moves, and audited end to end. GraphLogic turns AI from the thing your security team blocks into an asset they'll sign off on.
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AGENT CONTRACT · MARKET SCAN
Autonomy tierAnalyst
Drafts and analyzes freely. Publishing needs human sign-off.
Token budgetOn track
1.2M of 2M used. Signals at 80%, hard stop at 100%.
Active guardrails
Read-only data sources
No writes to production data
Escalate any spend over $50K
Status
Running
The problem
AI agents are powerful. Ungoverned, they're a liability.
The capability is ready. What stalls every enterprise AI project is the same three questions from security, finance, and legal, and "trust us" isn't an answer.
Runaway spend
An agent left to "reason until done" can burn through a budget overnight. Nobody wants a surprise six-figure AI bill.
Uncontrolled data access
Generic AI writes straight to your systems. Once it can mutate production data on its own, the blast radius is your whole graph.
No accountability
When the AI does something costly or wrong, "why did it do that?" has no answer. That's a non-starter in a regulated shop.
How it works
Autonomy, on a leash you set.
Four controls turn "we can't let AI act" into "AI acts, within rules we can audit."
01
Set the rules once, everywhere
Agent behavior is versioned, composable policy, not prompt-wrangling. Change "always cite sources" or "escalate over $50K" once, and every agent in every context inherits it.
Proof: a layered directive stack, resolved per context and logged.02
Cap the spend by design
Every agent runs under a token, cycle, and time budget, with signals at 80% and 95% and a hard stop at the limit. No runaway loops, no surprise invoices.
Proof: budget-aware invoker that pre-gates every call and meters usage.03
Keep humans in the loop where it counts
AI-generated data never lands in production unreviewed. High-stakes actions require sign-off; low-stakes work flows through. You set the line by tier and artifact type.
Proof: human-gated curation plus tiered trust (Scribe / Analyst / Advisor).04
Prove exactly why it acted
Every reasoning move and tool call is recorded in a replayable trail, and an agent is structurally incapable of a tool it wasn't granted, even if something tries to talk it into one.
Proof: reasoning-provenance log plus capability-based tool authorization.
DIRECTIVE STACK · RESOLVED
PlatformAlways cite sources
ProfileEscalate spend > $50K
LensRisk: require 2 sources
PhaseAct: approve before publish
SolutionRead-only production
ToolMax 500-node traversal
Rules compose top-down. The agent obeys all of them, and you can see which fired.
What it means for you
AI your security team will sign off on.
Governance stops being the reason AI projects die in committee, and becomes the reason they ship.
Data control
Your data stays yours
Nothing an agent produces reaches production without review. The organization stays the gatekeeper of its own graph.
Safe by default
Conservative on high stakes
Tiered trust keeps sensitive work approval-gated automatically, so the riskiest actions are never the unattended ones.
Auditable
Prove every action
A replayable trail answers "why did the agent do that?" precisely, exactly what an auditor or regulator needs to see.
Ready to let AI act, safely?
See how GraphLogic gives your agents real autonomy inside rules your security, finance, and legal teams can audit and trust.
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