Insify's SmartGuide helps self-employed choose disability insurance in a quick, human chat

Insify's SmartGuide turns clunky AOV choices into a quick, human-like chat that clarifies cover and routes to an expert when needed. Faster quotes, cleaner data, fewer drop-offs.

Categorized in: AI News Insurance
Published on: Nov 15, 2025
Insify's SmartGuide helps self-employed choose disability insurance in a quick, human chat

AI Tool of the Week: Insify's SmartGuide brings human-like advice to disability insurance for the self-employed

Disability insurance for freelancers and sole proprietors is full of friction: confusing terms, hard trade-offs, and drop-offs before quote. Dutch startup Insify has rolled out SmartGuide, an AI assistant that turns those steps into a simple, human-like chat. The goal is clear-get the right AOV cover in fewer steps, with clearer choices and less guesswork.

If you work in insurance-product, distribution, underwriting, or broking-this is the kind of tool that can shorten quote times, lift conversion, and still keep you covered on compliance.

What SmartGuide is (and isn't)

SmartGuide is a conversational interface that helps the self-employed choose disability cover through a guided Q&A. It doesn't replace advice where advice is required. It speeds up discovery, educates, and routes the customer to the right product and, if needed, a human expert.

Learn more about the company here: Insify.

Why this matters for insurance teams

  • Reduce friction: Replace long forms with a chat that clarifies key choices (benefit, waiting period, duration, indexation).
  • Better triage: Spot misfit risks early and route to human or alternative products before pricing work starts.
  • Cleaner data: Capture structured inputs for pricing, prefill, and underwriting notes in one flow.
  • Higher quality decisions: Explain trade-offs in plain language so customers pick cover that actually fits income volatility.

How the chat likely works in practice

  • Collects basics: occupation, income, business structure, age, health disclosures at a high level.
  • Explains trade-offs: benefit vs. premium, elimination period length vs. price, own-occupation definitions, exclusions.
  • Prefills quote: Pushes clean data to pricing and generates draft terms for review.
  • Handoff: Flags edge cases (complex medical history, mixed income) for a human to complete.

Key choices it should clarify for AOV

  • Benefit amount: Fixed sum or income-linked, plus indexation.
  • Waiting period (eigen risico): 30/60/90/180 days and the impact on premium.
  • Coverage definition: Own-occupation vs. broader definitions and claim triggers.
  • Duration: End age (e.g., 60/65/67) and renewability.
  • Exclusions and limitations: Back issues, mental health, pregnancy, hazardous work.

Compliance, controls, and auditability

  • Clear scope: Distinguish between information, guidance, and advice. Use scripted disclaimers where required by local rules.
  • Audit log: Store chat transcripts, versions, prompts, and outputs with timestamps.
  • Fairness: Test for biased prompts or outcomes across occupations and demographics.
  • Fallbacks: If confidence drops or health disclosures get complex, hand off to a licensed advisor.
  • Privacy: Minimise sensitive data in free text. Mask, encrypt, and set retention periods.

Metrics that matter

  • Quote time: First touch to bind-ready terms.
  • Completion rate: Started chat to quote generated.
  • Suitability: Post-bind fit vs. income and claim performance.
  • Drop-off reasons: Where and why customers leave the flow.
  • Complaint rate: Especially around misunderstanding of waiting periods and exclusions.

Rollout checklist for insurers and brokers

  • Define chat scope: Discovery only, or discovery + suitability guidance with human review.
  • Product rules: Encode eligibility, occupation classes, and medical knockouts.
  • Pricing integration: API to rating engine with guardrails on missing or inconsistent inputs.
  • Content library: Plain-language explanations for AOV concepts with approved phrasing.
  • Escalation paths: Warm transfer to licensed advisors with full context.
  • Accessibility: Mobile-first, multilingual, clear typography, and WCAG basics.
  • Testing: Red-team prompts, adversarial inputs, and edge-case journeys before launch.

Customer education still matters

Many self-employed people skip AOV because they don't know what to choose or what it costs. A guided chat can explain the basics in minutes and reduce bad choices that lead to disputes later. For a neutral primer on AOV for the self-employed, see the Dutch government's overview: business.gov.nl: Disability insurance for the self-employed.

What to watch next

  • Deeper underwriting: Structured health Q&A that stays compliant and sensitive.
  • Income verification: Secure links to tax data or bank feeds to cut friction.
  • Claims support: Chat that helps customers report, document, and track claims without confusion.
  • Broker tools: Co-pilot features that summarise chats, suggest next actions, and produce suitability notes.

Bottom line

SmartGuide is a practical step forward for AOV distribution. Fewer forms. Fewer "I'll do this later" moments. Clearer choices. This is where a lot of insurance journeys are heading-human where it counts, smart automation where it saves time and removes doubt.

If your team is building similar flows and needs structured upskilling on AI-assisted advisory, explore role-based training here: Complete AI Training: Courses by Job.


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