AI Platform for Commercial Insurance Brokers
Prioritize renewals, surface growth, support market access, and reduce manual work, with every recommendation reviewed by professionals.
Four priorities, one accountable workflow
An AI platform for commercial insurance brokers applies insurance-specific intelligence to brokerage data and workflows. It helps teams prioritize renewals, surface growth opportunities, support market access, and reduce manual work while brokers review recommendations and decide what action to take.
- Client retention Brokerage job: focus renewal work. Signal: approved policy and workflow data. AI-supported action: identify renewals needing attention. Human review: account teams apply client and coverage context. Measure: focus, outreach timing, and retention against a baseline.
- Organic growth Brokerage job: find relevant growth. Signal: approved account, coverage, and workflow relationships. AI-supported action: surface an opportunity and needed context. Human review: producers and account teams decide relevance and outreach. Measure: reviewed opportunities and resulting activity over a stated period.
- Market access Brokerage job: identify viable market options. Signal: confirmed carrier appetite, market, and submission data. AI-supported action: organize possible matches. Human review: the broker validates fit and placement strategy. Measure: market-selection efficiency within the verified scope.
- Productivity Brokerage job: manage daily priorities. Signal: approved tasks and workflow events. AI-supported action: present concise context and a clear next step. Human review: the professional chooses and owns the action. Measure: capacity, consistency, or processing time against a baseline.
How Alkeme AI turns brokerage work into clear action
Alkeme AI uses approved data inside a defined workflow, explains why work was flagged, gives the responsible professional a next step to review, and measures the selected outcome.
Broker-built, not carrier-centric
Alkeme AI is shaped inside a national brokerage to fit commercial insurance work. It supports retention, growth, productivity, and decision quality without hiding professional accountability.
- Use permissioned data Define the brokerage job, approved data scope, workflow trigger, and intended outcome before recommendations are produced.
- Identify and explain Apply insurance intelligence to flag a priority or opportunity, explain why it surfaced, and present a clear next action.
- Require human review The broker or account team applies client, coverage, and market context before deciding whether and how to act.
- Measure performance Compare retention, growth, capacity, or processing time with a defined baseline, population, scope, and time frame.
Core commercial insurance use cases
A clear next action for each brokerage team
- Agency owners and executives Connect retention, capacity, growth, and productivity to defined measures. Use verified results to assess responsible growth and agency value, while keeping goals separate from measured outcomes.
- Producers Focus preparation on reviewed growth opportunities and clearer client context. Decide whether an opportunity is relevant, what information is missing, and whether outreach is appropriate.
- Account teams See which renewals need attention first, understand why each item was flagged, and choose the next action using client, coverage, and service context.
- Operations leaders Define consistent workflows and review ownership, reduce repetitive work where verified, and measure capacity or processing time across an agreed population and period.
Responsible AI that keeps brokers in control
Alkeme AI is decision support, not autonomous brokerage. Permissioned data, reviewable recommendations, human approval, and defined measurements keep work accountable.
- Insurance expertise first Start with a genuine broker or client job.
- Proof over promises Use verified outcomes with scope and time frame.
- People remain accountable AI informs; insurance professionals decide.
- Trust by design Protect data and make recommendations reviewable.
- Progress through simplicity Fit intelligence into existing work.
Plan a measurable implementation
Start with one workflow, an approved data scope, a named review owner, and a baseline. Expand only after requirements and results are verified.
- Define the workflow Document the brokerage job, trigger, next action, review step, owner, and desired outcome.
- Confirm data and integrations Validate permissioned data, system requirements, available integrations, and the capability scope.
- Review controls and ownership State data use, access, auditability, recommendation limits, and the professional responsible for approval.
- Set the baseline and reporting plan Choose retention, growth, capacity, or processing-time measures with a defined population and time frame.
Frequently asked questions
Straight answers about renewals, growth, market access, productivity, data use, professional review, and measurable performance.