The #1 pricing and underwriting platform for commercial P&C insurance.
Morning, Mia. I have
4 submissions for you to review.
Reason over your underwriting context.
Reason over your underwriting context.
Hyperoperator ensures AI agents understand and follow your pricing logic, appetite rules, referral paths, permissions, historical decisions, documentation, wording libraries, and more.
Govern every action.
Govern every action.
Set when agents act, escalate, or stop. Configure straight-through, human-in-the-loop, and human-over-the-loop workflows by line of business, authority level, stage, and risk type.
Execute across the work.
Execute across the work.
Chain triage, enrichment, appetite checks, pricing, portfolio impact, and referral into governed workflows. Hyperoperator enables agents to operate the tools you use everyday.
Elevating the craft of underwriting
Elevating the craft of underwriting
Underwriters need to make high-stakes decisions across fragmented submissions, pricing tools, appetite rules, and portfolio data. Hyperoperator empowers them with teams of AI agents that can prepare risks, run models, check appetite, flag exceptions, and route decisions for review.
Underwriters need to make high-stakes decisions across fragmented submissions, pricing tools, appetite rules, and portfolio data. Hyperoperator empowers them with teams of AI agents that can prepare risks, run models, check appetite, flag exceptions, and route decisions for review.
Three modes
of operation
Three modes
of operation
Run recurring portfolio, renewal, and pricing workflows automatically.
Re-price
Re-price a renewal book overnight against updated market data.
Draft renewal terms within appetite, ready for review in the morning.
Refresh portfolio steering packs before weekly underwriting meetings.
Test, profile, and document models
Build sophisticated pricing, rating, appetite, and risk logic in native Python.
Use native data-frame support to make complex calculations easier to implement and faster to run.
Support modelers with built-in learning mode and reusable components.
Version and govern calculation logic
Profile model performance to identify bottlenecks and improve run times.
Test calculations before deployment to reduce model risk.
Generate and maintain documentation around model logic, assumptions, and changes.
Deploy calculations into your risk stack
Re-price
Re-price a renewal book overnight against updated market data.
Draft renewal terms within appetite, ready for review in the morning.
Refresh portfolio steering packs before weekly underwriting meetings.
Three modes
of operation
Run recurring portfolio, renewal, and pricing workflows automatically.
Re-price
Re-price a renewal book overnight against updated market data.
Draft renewal terms within appetite, ready for review in the morning.
Refresh portfolio steering packs before weekly underwriting meetings.
Test, profile, and document models
Build sophisticated pricing, rating, appetite, and risk logic in native Python.
Use native data-frame support to make complex calculations easier to implement and faster to run.
Support modelers with built-in learning mode and reusable components.
Version and govern calculation logic
Profile model performance to identify bottlenecks and improve run times.
Test calculations before deployment to reduce model risk.
Generate and maintain documentation around model logic, assumptions, and changes.
Deploy calculations into your risk stack
Re-price
Re-price a renewal book overnight against updated market data.
Draft renewal terms within appetite, ready for review in the morning.
Refresh portfolio steering packs before weekly underwriting meetings.
Three modes
of operation
Three modes
of operation
Run recurring portfolio, renewal, and pricing workflows automatically.
Re-price
Re-price a renewal book overnight against updated market data.
Draft renewal terms within appetite, ready for review in the morning.
Refresh portfolio steering packs before weekly underwriting meetings.
Test, profile, and document models
Build sophisticated pricing, rating, appetite, and risk logic in native Python.
Use native data-frame support to make complex calculations easier to implement and faster to run.
Support modelers with built-in learning mode and reusable components.
Version and govern calculation logic
Profile model performance to identify bottlenecks and improve run times.
Test calculations before deployment to reduce model risk.
Generate and maintain documentation around model logic, assumptions, and changes.
Deploy calculations into your risk stack
Re-price
Re-price a renewal book overnight against updated market data.
Draft renewal terms within appetite, ready for review in the morning.
Refresh portfolio steering packs before weekly underwriting meetings.
Run recurring portfolio, renewal, and pricing workflows automatically.
Re-price a renewal book overnight against updated market data.
Draft renewal terms within appetite, ready for review in the morning.
Refresh portfolio steering packs before weekly underwriting meetings.
Run recurring portfolio, renewal, and pricing workflows automatically.
Re-price a renewal book overnight against updated market data.
Draft renewal terms within appetite, ready for review in the morning.
Refresh portfolio steering packs before weekly underwriting meetings.
Test, profile, and document models
Build sophisticated pricing, rating, appetite, and risk logic in native Python.
Use native data-frame support to make complex calculations easier to implement and faster to run.
Support modelers with built-in learning mode and reusable components.
Test, profile, and document models
Build sophisticated pricing, rating, appetite, and risk logic in native Python.
Use native data-frame support to make complex calculations easier to implement and faster to run.
Support modelers with built-in learning mode and reusable components.
Version and govern calculation logic
Profile model performance to identify bottlenecks and improve run times.
Test calculations before deployment to reduce model risk.
Generate and maintain documentation around model logic, assumptions, and changes.
Version and govern calculation logic
Profile model performance to identify bottlenecks and improve run times.
Test calculations before deployment to reduce model risk.
Generate and maintain documentation around model logic, assumptions, and changes.
Deploy calculations into your risk stack
Re-price a renewal book overnight against updated market data.
Draft renewal terms within appetite, ready for review in the morning.
Refresh portfolio steering packs before weekly underwriting meetings.
Deploy calculations into your risk stack
Re-price a renewal book overnight against updated market data.
Draft renewal terms within appetite, ready for review in the morning.
Refresh portfolio steering packs before weekly underwriting meetings.
Three modes
of operation
Discover more
AI-powered decisions from triage, to pricing, to portfolio optimization
"By partnering with hx, we're making intelligent underwriting a reality for our Global Corporate & Specialty business"
Karen Dayal
Chief Underwriting Officer, Aviva
"By partnering with hx, we're making intelligent underwriting a reality for our Global Corporate & Specialty business"
Karen Dayal
Chief Underwriting Officer, Aviva
"By partnering with hx, we're making intelligent underwriting a reality for our Global Corporate & Specialty business"
Karen Dayal
Chief Underwriting Officer, Aviva
Underwrite Exponentially
Discover how hx puts pricing logic, underwriting judgment, portfolio intelligence, and governed agent execution into one platform.
