✦ Senior engineering for production systems
Best InsurTech in Rapid City
Build broker, carrier, renewal, claims, document, and deadline workflows with faster operations and traceable decisions.
A delivery system, not disconnected output
ArchitectureImportant boundaries and tradeoffs stay visible.
DeliveryWorking increments are reviewed against acceptance.
QualityTesting and release readiness are part of delivery.
OwnershipCode, documentation, and operational knowledge remain yours.
Where generic delivery breaks down
Insurance work crosses people, documents, carriers, deadlines, approvals, and systems that rarely share one consistent record. A fast interface does not solve the handoff and evidence problem.
Zenveus models the workflow, exceptions, integrations, permissions, communication, and audit needs before automating it.
The workflows we can build or improve
- Broker and customer onboarding
- Quote, submission, underwriting-support, and document flows
- Carrier, CRM, e-sign, and data integrations
- Renewal, upsell, lapse prevention, and communication
- Claims, SLA, deadline, escalation, and evidence
- Portals, permissions, dashboards, and reporting
Before work starts, we agree on the roles, data boundaries, integrations, exceptions, acceptance criteria, QA evidence, monitoring, and handoff. Those details determine whether the workflow can actually run in production.
Questions we usually hear before work starts
Can you integrate with carrier and broker systems?
Yes, subject to available APIs and access. We plan synchronization, retries, rate limits, reconciliation, monitoring, and operator recovery.
Can AI process documents safely?
AI can assist extraction, classification, drafting, and review when sources, validation, confidence, permissions, and human approval are designed into the workflow.
Can we modernize one workflow first?
Yes. A bounded onboarding, renewal, document, or SLA workflow can prove value without forcing a platform-wide replacement.
Need a senior technical opinion?
How we work through the domain
Follow the work as it happens today
We sit with the operators and domain experts who know where the process bends. Together we trace the people, decisions, evidence, exceptions, and systems involved, then agree on the result worth measuring.
Decide what the system must control
We make the control points explicit before they disappear into code: who can act, who owns the data, how integrations fail, what needs review, what gets audited, and how a milestone will be accepted.
Prove one complete workflow first
The first milestone covers one complete outcome, including the operator tools and exception handling needed to run it. We expand only after that path works under real conditions.
Release without creating dependency
Before launch, both teams agree on deployment, monitoring, incident response, credentials, documentation, intellectual property, and who supports the system next.
Work that relates to this problem
QubeRisk
Reduced repetitive entry and centralized commercial-insurance onboarding and broker operations.
Insurance Renewal Upsell
Reduced lapse from 11.4% to 4.1% and protected roughly $680K in annual premium.
SLA Deadline Watchdog
Reduced breach rate to under 5.5% and increased alert response to 96%.
Some Of Our Recent Work
AI & automationInsurance renewal automation cut lapse rates from 11.4% to 4.1%
Reduced lapse rate from 11.4% to 4.1%, protected roughly $680K in annual premium, added about $210K in new annual pre…
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Regulated systemCommercial insurance onboarding unified forms, underwriting, documents, and broker work
Reduced onboarding friction, minimized repetitive form entry, sped up internal evaluation, centralized broker workflo…
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AI & automationProactive SLA automation reduced breach rates below 5.5%
Reduced SLA breach rate from about 14% to under 5.5%, increased alert response from about 30% to 96%, cut manager pla…
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AI & automationEnterprise analytics inside the customer cloud — answers to dashboards in under 60 seconds
Turns natural-language questions into live dashboards in under 60 seconds and deploys inside the customer's AWS accou…
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AI & automationAI sales automation rebuilt for reliability — 80+ qualified leads a day
Scaled from 30-50 to 80+ leads/day, cut invalid records reaching AI to 0%, detected failures in under 30 seconds, and…
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SaaS & platformAthlete readiness unified across four data sources and three performance programs
Active deployment across two professional squads and one university performance program, processing real-time data fr…
Read the case study →What shapes the plan and price
The plan depends on the workflow, user roles, platforms, integrations, migration, review obligations, product maturity, and the cost of getting a critical path wrong. If those factors are still unclear, we start with a short audit or discovery phase. Defined work can move into fixed milestones; evolving products may need a named ongoing team.
The proposal names the people responsible for implementation, architecture review, QA, and delivery. Access starts at the minimum needed for the work. We agree on repositories, environments, credentials, documentation, and handoff before delivery begins.
Where engineering stops and client responsibility begins
Zenveus provides compliance-aware product engineering and works with client insurance and legal experts. It does not provide insurance licensing or legal certification.
Turn the way your team works into a buildable plan
Show us the current process, the people using it, the systems involved, and where work breaks down. We will recommend an audit, a defined build, an ongoing team, or a better alternative if software is not the first problem to solve.