No. IT is involved (they need to approve connections to your systems and review security), but this isn’t a multi-year infrastructure overhaul. This happens in weeks to months with a small IT team.
The 4-day quote is dead
Healthbus cut quote times from 4 days to real-time — without moving their data or replacing their systems. See how.
You’re losing deals to faster competitors
In a hard market, speed is your only competitive advantage.
While you spend days manually extracting data from PDFs and spreadsheets, your competitors are quoting faster, and binding the policy before you’ve even opened the submission email.
The cost of slow operations
- Lost revenue — Slow response equals lost opportunity. Speed is critical to even submit a proposal. If you’re not fast, you can’t bid.
- Margin erosion — Manual work is expensive. Every hour of data entry is an hour not spent on risk analysis.
- Employee burnout — Your underwriters spend a significant portion of their time on administrative tasks instead of the strategic work they were hired to do.
- Customer frustration — A multi-day quote delay means prospects shopping at renewal move to competitors.
The conventional solution
“Hire more people.” But headcount doesn’t scale. Neither does outsourcing. Your team is drowning in digital noise of endless documents, and throwing more humans at the problem just makes coordination harder.
What you actually need
AI that understands your business, not just your documents.
Three critical choke points across the insurance lifecycle
Every carrier faces these friction points. Which one is costing you the most?
The problem
Your intake channels are flooded with hundreds of submissions daily. Your team processes them “first in, first out,” wasting hours reviewing out-of-appetite risks while high-value opportunities sit buried at the bottom of the pile — until the requestor moves on.
The cost
- Adverse selection — You end up with the worst risks
- Missed revenue — Best risks go to competitors
- Wasted underwriter time — Team spend time reviewing junk submissions
The Kamiwaza fix: Context-aware triage
Digital co-workers read every incoming email and attachment instantly, scoring each submission against your specific appetite guidelines — for example, “Decline: Roof > 20 years,” or “Prioritize: Clean loss run.”
The outcome
- Stop adverse selection at the front door
- Route only prioritized, winnable business to your underwriters
- Dramatically reduce submission review time
The problem
Generating a complex commercial quote takes days because data must be manually extracted from disparate PDFs and Excel schedules, then re-keyed into your pricing model. By the time you respond, the broker or requestor has already bound elsewhere.
The cost
- Lost deals — Speed is the tiebreaker in commodity lines
- Limited quote volume — Can’t scale without more people
- Demoralized sales team — They know they’re too slow to compete
The Kamiwaza fix: Real-time quote generation
Digital co-workers automatically extract, structure, and map risk data from messy documents directly into your rating engine — without human intervention.
The outcome
- Quote dramatically faster
- Bind policies before competitors respond
- Significantly increase quote volume with same team size
The problem
Claims adjusters are forced to act as “archaeologists,” digging through underwriting files, policy documents, and medical evidence spread across multiple systems. This friction causes delays, inflates loss adjustment expenses (LAE), and churns customers who are frustrated by slow responses.
The cost
- Extended cycle times — Weeks to make coverage decisions
- Increased LAE — Every extra day of investigation costs money
- Customer churn — Policyholders leave after bad claims experience
The Kamiwaza fix: The golden thread
We build a live context graph that links the original underwriting intent to new claims evidence, instantly validating coverage and summarizing liability.
The outcome
- Valid claims paid fast, meaning customer satisfaction soars
- Invalid claims flagged instantly, reducing fraud losses
- Adjusters focus on judgment, not document hunting
Healthbus: From 4 days to real time
The challenge
Healthbus, a comprehensive benefits platform serving employers nationwide, faced the same scalability crisis you're experiencing: their manual quote generation process was taking too long.
Every quote required days of back-and-forth with clients to gather documentation, verify carrier requirements, and structure data for their pricing models. On average, it took 5 separate client touchpoints just to get a complete submission.
What Healthbus did differently
Instead of consolidating data or hiring more people, Healthbus deployed Kamiwaza to orchestrate across their existing systems without moving a single file.
The transformation
| What changed | Before Kamiwaza | With Kamiwaza |
|---|---|---|
| Quote speed | 4 days | Real time |
| Client friction | 5 touchpoints | 1 touchpoint |
| Manual data entry | Manual process | Zero manual entry |
The technical reality
This wasn’t a “rip and replace” IT project. Healthbus didn’t migrate data, didn’t replace their policy admin system, and didn’t fire their team.
They simply deployed digital co-workers that understood their business context — which carriers offer which plans, what documentation is required for each, how to validate employer group structures — and automated the administrative burden that was drowning their humans.
“Kamiwaza transformed our entire sales workflow. What used to take 4 days of manual data gathering now happens in real-time. Our brokers are shocked — and our close rate proves it.” — VP of Operations, Healthbus
Innovation without disruption
No data migration. No system replacement. No multi-year IT project.
You’ve been told that to modernize your operations, you need to:
- Consolidate all your data into a cloud data lake
- Replace your legacy policy admin system
- Wait years for results
That’s wrong. Here's the reality: Kamiwaza doesn’t require you to move your data or replace your systems. We sit above your existing infrastructure and orchestrate action across it.
What this means for your operations
Step 1: We connect to your data where it lives
- Email servers — Submissions come in
- Policy administration systems — Your source of truth
- Document storage — Contracts, loss runs, and underwriting files
- Carrier portals — Rate sheets, eligibility rules
- Spreadsheets — Yes, even the Excel files your underwriters maintain
No data leaves your environment. We index relationships and business rules, not raw files.
Step 2: We learn your business context
This is the breakthrough. Traditional AI sees “Building A” and “Location 1” as unrelated text strings. Kamiwaza builds a living ontology that understands:
- “Building A” in the loss run is the same property as “Location 1” in the submission
- This employer group has a rating tier that requires specific underwriting approval
- This carrier only accepts groups over 50 employees in this state
- This type of claim requires evidence from both the underwriting file and the policy schedule
We automatically discover these relationships by observing how your team actually works — no months of “rules configuration.”
Step 3: Digital co-workers execute the workflows
Once we understand your data and your business logic, we deploy AI agents that:
- Read incoming submissions and score them against your appetite
- Extract data from PDFs and map it to your rating engine
- Link underwriting assumptions to claims evidence
- Route work to the right human when judgment is needed
They work around the clock. They never get tired. And they inherit your team’s exact permissions — if an underwriter can’t see sensitive medical records, neither can their AI agent.
Timeline to impact
This happens in weeks to months, not years.
The old way versus the Kamiwaza way
| Traditional AI transformation | Kamiwaza | |
|---|---|---|
| First step | Consolidate data into a data lake (takes years) | Connect to data in place (takes weeks) |
| IT dependency | Massive infrastructure overhaul required | Works with existing systems |
| Business disruption | High — migration risks, system downtime | Zero — orchestrates above existing infrastructure |
| Time-to-value | Years, if it succeeds at all | Weeks to months |
| What AI understands | Keywords and document retrieval | Business context, relationships, rules |
| Scalability | Requires more IT budget for each new use case | Compounds — each workflow makes the next one faster |
Frequently asked questions
Will this require a big IT project?
What if our data is messy?
That’s exactly what we solve. Most insurers have messy data — inconsistent formats, hand-written notes, missing fields, legacy codes that only veteran employees understand. Kamiwaza’s living ontology learns how to interpret your data by observing how your team uses it.
How accurate is the AI?
Healthbus achieved zero errors requiring manual correction. Why? Because the AI understands business context, not just keywords. It knows the difference between “this document is relevant” and “this document satisfies the business requirement.”
Can we customize it for our specific workflows?
Yes. Every insurer has unique appetite guidelines, carrier relationships, and underwriting philosophies. Kamiwaza adapts to your business rules — we don’t force you into a generic template.
Ready to quote in real time?
Schedule a consultation to see if Kamiwaza fits your workflows.
We move with you.
We don’t ask you to reshape your world to fit AI — we bring AI to your world. That means flowing into your existing systems, silos, and security processes. No forced centralization, no compromise. Just intelligence that integrates, not interrupts.
We build for altitude, not just output.
We build for growth, for innovation — and not just functional output. We’re not just connecting data sources or streamlining steps: we’re building a path for better decisions, faster thinking, and less overhead.
We believe in results over hype.
We track, quantify, and optimize outcomes, backing you up with close collaboration and hands-on support. So you can clearly see the ROI. Because AI isn’t just about innovation buzzwords — it’s about real, measurable business impact.