Enterprise risk × prediction markets
Argovis AI brokers convert enterprise exposures into binary YES/NO questions, documented rules, and evidence packages. If an external prediction marketplace lists the contract, each participant trades there under the venue’s rules.
For risk buyers
Start with the financial exposure. Argovis converts it into a binary event, a contract quantity, an observation window, and settlement rules.
For risk capital
Review the same binary contract, source hierarchy, model, uncertainty, and maximum loss that the enterprise buyer reviews.
The proposed workflow
Start with a material enterprise exposure and a measurable event.
Draft one binary question, observation window, source, and edge-case rules.
Test source continuity, historical outcomes, model limits, and basis risk.
Freeze the contract version and prepare buyer and capital decision briefs.
Record conditional, non-binding side, price, and quantity interest.
The marketplace decides whether to list. Participants then trade independently.
Argovis does not place orders, hold funds, match counterparties, or settle contracts.
Who we serve
Enterprise risk leaders define the exposure. Event-contract traders and market makers evaluate the same question from the other side.
Captives, business interruption, and enterprise risk financing.
Grid, hail, heat, outage, and uptime risk.
Algae blooms, water quality, and service disruption.
Closure, congestion, and supply chain interruption.
Market makers and risk capital evaluating YES and NO positions.
The parameter factory
Combine public, private, and sensor data into an auditable trigger. Give the buyer, risk capital, and marketplace the same question and evidence.
Asset, location, event, observation window, protection target, and operational need.
Satellite, agency, sensor, alert, telemetry, and counterparty data.
Binary YES/NO test, source priority, fallback rules, and dispute process.
Historical replay, modeled probability, price sensitivity, and basis-risk analysis.
The venue applies its published rules and settles the winning side in U.S. dollars.
Listed-market example
Kalshi lists seven binary markets for 2026 ERCOT peak demand. Each market uses a different threshold. An enterprise can assess whether one of these listed outcomes relates to its own grid exposure.
Kalshi resolves this market to YES if ERCOT reports a full-hour integrated system load above 91,500 MW during calendar year 2026. The official settled ERCOT value controls the result.
View the listed Kalshi event| Venue result | Rule result | 10,000 YES contracts |
|---|---|---|
| YES | ERCOT reports an official settled full-hour peak above 91,500 MW for 2026. | $10,000 enters the account cash balance. The amount above the $700 contract cost is $9,300, before fees. |
| NO | The official settled 2026 peak does not exceed 91,500 MW. | $0 settlement. The $700 contract cost is lost, plus applicable fees. |
*Kalshi displayed a $0.07 YES ask for the 91,500 MW market when Argovis reviewed it on September 10, 2026. Prices, available quantity, spreads, and fees can change. The 10,000-contract order and its $700 cost are an example; they are not an executed trade or an offer. Kalshi states that a winning contract settles at $1 and a losing contract settles at $0. Settlement credits U.S. dollars to the participant’s account cash balance. This contract follows ERCOT’s official settled data. It does not settle on a company’s outage or financial loss. View the ERCOT source · Read the Kalshi settlement guide
Argovis role
Map an enterprise exposure to the listed thresholds, test basis risk, compare a model probability with the market price, and record the participant’s review.
Marketplace role
List and operate the market, accept participant orders, apply the published ERCOT rule, determine the outcome, and settle positions in U.S. dollars.
Process boundaries
Participants define the event, review evidence, test the model, approve a version, and record non-binding interest. No order or position is created.
The venue reviews the proposal and decides whether to list it. Its rules control trading, market determination, disputes, and U.S. dollar settlement.
After listing, each participant independently chooses YES, NO, or no trade. Argovis has no authority to place the order or hold the participant’s funds.
Risk universe
Candidate parameters span infrastructure, the environment, logistics, grid disruption, conflict, and cyber-physical events. Each needs defensible data and an agreed trigger.
ERCOT, utility outage feeds, heat index, hail radar, facility uptime, and backup-power telemetry.
Satellite bloom data, local water agencies, field sensors, closures, and raw-water quality thresholds.
Thermal anomalies, satellite imagery, local air-defense alerts, and facility reports.
Vessel tracking, berth closures, vessel queues, port notices, and cargo dwell time.
Fires, chemical plumes, agency alerts, environmental sensors, and satellite confirmation.
Network and incident feeds, uptime logs, control-system data, cloud disruption, and operator attestations.
AI broker network
Argovis uses artificial intelligence (AI) brokers under human supervision to find risks, assemble evidence, draft outreach, and prepare proposed products.
Finds assets, stress signals, buyer needs, and relevant data sources.
Turns a risk description into candidate binary questions and contract rules.
Prepares source priority, historical replay, risk analysis, and quote evidence.
Records aggregate, non-binding interest by side, price, quantity, and mandate.
Collects event evidence and tracks the venue’s determination and settlement record.
Example risk inventory
These examples show the enterprise exposure, possible settlement rule, and potential YES/NO market. They are research examples, not listed markets or offers.
| Enterprise risk | Possible settlement rule | Possible buyer side | Market review |
|---|---|---|---|
| Texas data center grid interruption | Defined ERCOT alert, local outage duration, and official source hierarchy. | Buy YES contracts for the qualifying interruption. | Evaluate YES or NO using price, model probability, basis risk, and liquidity. |
| Reservoir algae bloom | Defined satellite index, agency advisory, and persistence threshold. | Buy YES contracts for the qualifying bloom. | Review source continuity, seasonality, false positives, and contract price. |
| Port disruption | Defined port closure, vessel queue, and cargo dwell-time threshold. | Buy YES contracts for the qualifying disruption. | Review event correlation, observation window, and available order-book depth. |