End-to-End Insurance AI Agent
Budget: $5,000 – $10,000 USD
I’m ready to deploy an AI-driven agent that will take the heavy lifting out of our day-to-day brokerage workflow. The solution needs to plug smoothly into our Email, CRM software, insurance policy-management platform, as well as our public-facing website and other lead sources so it can act on real data the moment it appears.
Core capabilities I need built and finely tuned:
• Lead generation and qualification – capture prospects from every digital touchpoint, enrich them inside the CRM, and push real-time alerts to the sales team.
• Quote intake and generation – pull risk data, pre-fill carrier forms, and return bindable quotes without manual re-keying.
• Email management – draft, send, and file messages while maintaining conversation history for both clients and internal staff.
• Policy renewal analysis & recommendations – surface upcoming renewals, compare market alternatives, and flag savings or coverage gaps.
• Client service requests – track endorsements, certificates, and coverage changes, then route tasks to the right teammate or complete them automatically.
Interaction scope covers client-facing conversations, back-office collaboration with our internal team, automated notifications, plus smart prompts for our brokers so nothing slips through the cracks.
Acceptance criteria
1. Seamless two-way API connections to the stated platforms with no data loss.
2. Demonstrable workflows for each core capability running end-to-end in a staging environment.
3. Clear documentation (architecture, setup, and user guides) that my team can follow without outside help.
If you’ve previously orchestrated insurance or finance-sector automations using NLP, RPA, or tools such as Dialogflow, LangChain, or custom Python/Java microservices, I’d like to see live examples. Let’s modernise our brokerage together.
Core capabilities I need built and finely tuned:
• Lead generation and qualification – capture prospects from every digital touchpoint, enrich them inside the CRM, and push real-time alerts to the sales team.
• Quote intake and generation – pull risk data, pre-fill carrier forms, and return bindable quotes without manual re-keying.
• Email management – draft, send, and file messages while maintaining conversation history for both clients and internal staff.
• Policy renewal analysis & recommendations – surface upcoming renewals, compare market alternatives, and flag savings or coverage gaps.
• Client service requests – track endorsements, certificates, and coverage changes, then route tasks to the right teammate or complete them automatically.
Interaction scope covers client-facing conversations, back-office collaboration with our internal team, automated notifications, plus smart prompts for our brokers so nothing slips through the cracks.
Acceptance criteria
1. Seamless two-way API connections to the stated platforms with no data loss.
2. Demonstrable workflows for each core capability running end-to-end in a staging environment.
3. Clear documentation (architecture, setup, and user guides) that my team can follow without outside help.
If you’ve previously orchestrated insurance or finance-sector automations using NLP, RPA, or tools such as Dialogflow, LangChain, or custom Python/Java microservices, I’d like to see live examples. Let’s modernise our brokerage together.