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© Jonatas Gaigher · Senior Product Designer

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20262026Senior Product Designer @ Howden

An AI that insurance brokers can sign their name under.

Howden Vantage is a workspace for insurance brokers, built on top of Applied Epic. Through Layline, I designed it and its AI, Howden Intelligence, and prototyped every flow in code: the morning brief, citations, the approval loop, AI permissions and a way to read accounts with hundreds of policies, locations and vehicles.

Role
Senior Product Designer
Team
Layline Design Co., for Howden
Timeline
2026 – 2026
Platform
Web app
Silhouettes at a reception desk in front of a lit wall with the Howden logo in pistachio green
  • 4

    Prototype versions in code, in two weeks

  • 30s

    To pull back anything the AI sent

  • 212

    Vehicles in the fleet stress test

On this page

  1. 01Context
  2. 02The problem
  3. 03Approach
  4. 04Citations
  5. 05Show, check, approve
  6. 06AI Toolkit
  7. 07Big accounts
  8. 08Changes
  9. 09The stress test
  10. 10Outcome
  11. 11What I learned

01

Context

A broker’s day is spread across Applied Epic, Outlook, SharePoint and a stack of carrier PDFs.

Howden is one of the largest insurance brokers in the world. Vantage is the workspace its brokers would open first thing in the morning, sitting on top of Applied Epic, where policies and clients live, and bringing in the quotes, emails and spreadsheets the work actually happens in.

At the centre of it is Howden Intelligence, an AI that reads all of that and drafts the next step. I designed the workspace and the AI through Layline Design Co., and built it as a working prototype the team could click through instead of a set of frames.

Every client, policy and number in this case is fictional.

02

The problem

Drafting binding instructions is easy for an AI. Getting a broker to send them is the hard part.

In insurance, a wrong number in a binding instruction isn’t a typo. It’s a coverage gap with a client’s name on it. So the questions from Howden’s side weren’t about what the AI could do, but about whether anyone could rely on it. They came down to three worries.

  1. 01

    Can I trust what it says?

    If the AI drafts something, the broker needs to see what it did, check it, and be able to take it back.

  2. 02

    Documents are the source of truth

    A quote PDF or a schedule of values outranks any summary, so the documents have to be one click away from every claim.

  3. 03

    Accounts are huge

    A manufacturer has dozens of policies across plants, fleets and the company itself. Seeing them without drowning was its own problem.

03

Approach

I prototyped in code, not in frames, so every review was a click-through with real flows.

The sandbox started from the Howden Figma file and an earlier ideation round. Version 1 rebuilt the workspace in code, with a dense home of renewals, calendar and to-dos. Version 2 tried a green shell. Version 3 put four directions for Home and the client page side by side, and “Just chat” won: a short brief in place of a dashboard.

Version 4 answered the three worries one by one. Each version lives at its own URL, so the team could compare them and come back to any of them, and the approved front end is written to be carried into production.

[fig 3.1] From an earlier ideation, to a dense first version, to the brief that shipped in v4

04

Citations

Every claim says where it came from, down to the page or the cell.

The morning brief tells Natalie what matters today: Castlewood, and one thing that’s already late. Each fact in it carries a small mark with its source, like “Chubb quote · p.2”.

Resting on the mark shows the exact passage. Clicking it opens the document beside the work, scrolled to that passage and highlighted, so checking a claim never means losing your place.

[fig 4.1] From the claim to the passage to the document, without leaving the brief

05

Show, check, approve

The AI shows its work, the broker checks it, and only then does anything leave.

“Review my draft” opens the binding instructions to Travelers, Chubb and The Hartford, with every number tied to its quote. When two documents disagree, the AI says so in words. The Dayton plant is $21.2M in the Travelers quote and $18.4M in the schedule of values, so it puts them side by side, says which it would use and why, and leaves the choice to the broker.

Each line has its own check against its source, and nothing is sent until the broker approves. Once it goes, it’s logged on the to-do and can be pulled back for 30 seconds. After that it can only be corrected, which is how a broker already thinks about anything sent to a carrier.

[fig 5.1] Two documents disagree: the AI compares them and suggests, the broker decides
[fig 5.2] Check each line, approve, and keep 30 seconds to take it back

06

AI Toolkit

How much the AI does on its own is a setting, not a surprise.

AI Toolkit lists what Howden Intelligence can do, from filing incoming documents to updating records in Applied Epic, and lets each broker choose: does it alone, asks first, or never. Some are fixed by Howden policy. Sending email always needs a person, and binding coverage is never left to the AI.

The setting shows up in the work itself. Switch drafting to “Asks first” and the brief stops saying “I’ve drafted them” and starts asking “Want me to draft them?”

[fig 6.1] One setting, and the brief changes how it speaks

07

Big accounts

An account reads both ways: what’s insured, and what insures it.

Castlewood has 22 policies across three plants, a fleet and the company as a whole. The Policies tab reads in either direction. Start from what’s insured, and a plant shows every policy covering it. Start from a policy, and it shows what it covers. Click through and you land on the other side.

Flags travel with the data. The Dayton plant carries the same dot everywhere it appears, because the schedule of values and the newer survey still disagree on what it’s worth.

[fig 7.1] From a plant to its policies, and from a policy back to the plant

08

Changes

A change shows everything it reaches before anyone approves it.

Adding a location is rarely just one record. Howden Intelligence finds the new east warehouse in the Dayton risk survey and fills it in. Then “What changes” lays out the reach: five policies, the plant, a to-do and a document, and about $8,400 a year more on property.

From there it writes the endorsement request to the four carriers, and it goes through the same check and approve as the binding instructions. One loop for every action the AI takes.

[fig 8.1] Fill, see the reach, write the request, approve

09

The stress test

Harborline’s fleet of 212 vehicles was where the design had to hold up.

Long lists lead with what changed. The trucking fleet opens with the three vehicles that moved since the last schedule went to the carrier, and the other 209 are one search away instead of one long scroll.

[fig 9.1] What changed first, the other 209 a search away

10

Outcome

One loop for everything the AI does: show the source, let the broker check, approve, log, undo.

The three worries became three patterns that the rest of Vantage reuses: citations that open the document, an approval that’s logged and can be pulled back, and an account you can read from either side.

Because the prototype is code, the team reviews real behaviour instead of describing it, and the approved front end is ready to be carried into the product.

11

What I learned

Trust is a feature you design, not a disclaimer you add. “Howden Intelligence can make mistakes” only means something when the next click shows you where to check.

Prototyping in code changed the conversation. Hard questions like what happens when two documents disagree, or what one new location touches, got answered by clicking through them, not by debating a frame.

Next case

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Giving men a place to ask for help without it feeling like asking for help.

→