Pre-flight condition gate for AI agents

Your agents can execute.
Do they know when they should?

Presigate is the pre-flight decision gate that tells autonomous AI agents whether conditions are right to act — before they execute.

GSI Signal

ACT

Conditions favorable

GSI Signal

HOLD

Regime mismatch

GSI Signal

ESCALATE

Data integrity fail

The problem

Autonomous agents can execute.
They cannot sense conditions.

AI agents are moving from recommendation to execution. They have real authority — to buy, commit, transfer, and transact on your behalf. But the frameworks built to govern agents are focused almost entirely on what agents should do — not on whether external conditions are right for them to act right now.

There is no standard layer that gives an agent a structured, real-time read of whether the environment it is about to act in is safe, stable, and favorable. That missing layer is costing money today. As agent autonomy expands into procurement, payments, and portfolio management, the blast radius of un-gated execution grows with it.

The precedent

Smart contracts needed oracles. Agents need a condition gate.

Smart contracts execute autonomously — but they cannot see outside their own environment. Without an external layer verifying real-world conditions, they acted on stale or wrong data. The results were documented and dollar-denominated. The industry's answer was the oracle: mandatory verification infrastructure that became non-negotiable before any serious system would launch.

Presigate is the structural equivalent for the AI agent economy. Not a price feed — a condition gate. A real-time answer to "are conditions right to act right now?" delivered as a signal layer before the agent executes.

Documented losses from un-gated execution

Flash Crash

2010

>$1T intraday

An algorithm sold $4.1B in futures contracts with no read on whether the market could absorb it. Liquidity evaporated. The Dow fell 1,000 points in minutes — not because of bad data, but because the system checked no condition between its intent and its execution.

Knight Capital

2012

$457.6M

A decommissioned trading strategy reactivated with no condition gate. In 45 minutes, the firm accumulated $3.5B in erroneous positions. A 17-year-old firm was forced into acquisition because there was no check between decision and execution.

Lobstar Wilde AI

2026

~$440K

An autonomous AI agent's session reset invalidated its state. No gate verified the operating context was still reliable before execution. It transferred $440,000 in value against stale, reset state.

How it works

Five intelligence primitives.
One gate signal.

Before your agent acts, Presigate runs five structured checks — each answering a distinct question about current conditions. The results feed into a single composite gate output: act, hold, or escalate.

RXI

Regime eXecution Intelligence

"Is the environment stable, trending, or chaotic?"

Real-time environment classification so agents know whether their strategy is operating in the conditions it was designed for.

MMI

Market Microstructure Intelligence

"Is the execution medium liquid, fairly priced, and absorptive right now?"

Live depth, spread, and price-impact assessment before any action commits resources.

CSI

Composite Sentiment Index

"Is the crowd aligned with or against this action?"

Aggregate behavioral signal that tells the agent whether it is acting with or against prevailing conditions.

DIV

Data Integrity Validator

"Can I trust the data I am about to act on?"

Freshness checks, anomaly detection, and feed-health monitoring — the oracle-integrity layer that catches bad inputs before they become bad actions.

GSI

Gate Suitability Index

Aggregates RXI + MMI + CSI + DIV

"Given all of the above — act, hold, or escalate?"

The composite go/no-go gate. Aggregates RXI, MMI, CSI, and DIV into a single actionable signal. This is the gate every agent queries.

ACT — conditions favorable HOLD — one or more signals off ESCALATE — human review required

Why now

The picks-and-shovels layer the agent economy is missing.

Autonomous agents are being deployed with real execution authority — wallets, APIs, spend limits, and decision-making power their operators have granted them. The infrastructure for what agents do is maturing fast: orchestration frameworks, memory layers, tool-calling specs.

The infrastructure for when agents should act does not exist yet. That gap is where preventable losses happen — and where the first serious wave of agentic AI failures will be documented, named, and dollar-denominated. Presigate is built to be the standard layer before that curve completes.

The pattern

Optional to mandatory follows a consistent arc

A capability becomes available. Early adopters deploy naively. Preventable failures create documented losses. The industry converges on a standard layer. The condition-gating layer for agents is at the beginning of that arc — with a broader deployment surface and higher stakes per failure than the markets proved out.

The opportunity

Whoever defines the standard owns the layer

This is not currently a standard — it is a competitive advantage for builders who take it seriously first. The question is not whether condition-gating becomes mandatory infrastructure. The question is whose name is on it when every serious agent deployment has one.

The proof

Built on the hardest proving ground

Presigate's signal layer is built on real-time financial execution — the domain where errors are immediate, irreversible, and dollar-denominated. Every primitive is validated against conditions where failure has a named incident and a documented loss attached to it.

Early access

Be first when the gate opens.

Presigate is in private development. We are selectively onboarding AI agent teams and infrastructure partners who want to integrate condition-gating before it becomes table stakes.

Or reach us at hello@presigate.com