tigerlab

tigerlab We deliver insurance innovation for your business.

August is quiet across the market. We’re using it to build.While things slow down, the team is heads-down on the work th...
20/08/2026

August is quiet across the market. We’re using it to build.

While things slow down, the team is heads-down on the work that matters most: making the our systems faster, cleaner, and ready for whatever Q4 throws at it.

No summer slowdown here.

bms

Most underwriters will tell you the risk assessment takes minutes. What takes days is everything around it.Sorting submi...
13/08/2026

Most underwriters will tell you the risk assessment takes minutes. What takes days is everything around it.

Sorting submissions, extracting data, chasing missing documents, re-keying information between disconnected systems.

Agentic AI is being positioned as the response. Not another chatbot, but a coordinated pipeline of specialised agents that hands a structured, decision-ready file to the underwriter.

This article covers how these systems actually work, how the hallucination risk is being addressed, and why regulatory and competitive pressures are making this urgent in 2026.

Read the full article through the link below.

Most broker systems come with a dependency nobody actually chose. The software keeps the records, but the work that move...
11/08/2026

Most broker systems come with a dependency nobody actually chose. The software keeps the records, but the work that moves a renewal forward still runs by hand. Someone re-keys the same details from one carrier portal to the next. Someone chases the data that never turns up in a usable format. Do that long enough and the knowledge settles into the people who hold it, until the process is really just a handful of individuals who know where everything lives.

You feel it most in summer. When the handler who knows a book takes a fortnight off, the renewals do not pause with them. They keep arriving on schedule and then sit, because the system was never moving them. The person was.

By September the delay comes due. Data gets chased late and quotes go out behind schedule, and then come the apologies. Most clients will forgive a late renewal, but a lapse in cover, or an apology for one, is the kind of thing that makes a good client start wondering what else they are missing, and makes it easier for someone else to step in.

This is what legacy tech quietly builds. A system that runs only as long as the right people are there to carry it. August is simply when you find out how much they were carrying.

tigerlab's BMS is built to carry that weight itself. Renewals are staged ahead and carrier data is normalised as it arrives, so the work keeps moving on its own instead of waiting for the one person who knows where it lives. The people can take the break. The pipeline does not have to.

Broker technology decisions rarely go wrong at the point of purchase. They go wrong earlier, in the assumptions that sha...
06/08/2026

Broker technology decisions rarely go wrong at the point of purchase. They go wrong earlier, in the assumptions that shape the shortlist, and later, in the months after go-live when nobody owns the platform anymore.

We have set out three patterns we keep seeing, including why staying with an older system is sometimes the right call, and the three questions that tell you more about long-term fit than a feature list ever will.
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Find the full article in the comment section below.

Brokers, we know the feeling. Setting your out-of-office in August shouldn't feel like abandoning ship. But it does, whe...
04/08/2026

Brokers, we know the feeling.

Setting your out-of-office in August shouldn't feel like abandoning ship. But it does, when your quote lives in one portal and the client record in another and neither has ever spoken to the carrier. A week off just means coming back to a mountain of backlog.

You shouldn't pay for a summer holiday with a September panic.

tigerlab's BMS keeps the engine running when you step away. With true API-first connectivity, your systems finally talk to each other. The workflows automate. The carrier data syncs. The manual re-keying disappears.

Enjoy the time off. Let the core system handle the rest. 🏖️

Happy Swiss National Day! 🇨🇭🏔️Wishing our entire Swiss network a wonderful holiday. Whether you are getting ready for th...
01/08/2026

Happy Swiss National Day! 🇨🇭🏔️

Wishing our entire Swiss network a wonderful holiday. Whether you are getting ready for the bonfires tonight or just spending quality time offline with family and friends, have a fantastic weekend.

En guete and enjoy the celebrations! ✨

You find out on a Monday. One carrier's rates aren't pulling into the quoting screen and nobody on your side touched any...
30/07/2026

You find out on a Monday. One carrier's rates aren't pulling into the quoting screen and nobody on your side touched anything, because it was the carrier who quietly moved an endpoint on Friday. The integration that worked all week returns nothing, and the only people who can fix it are the vendor's developers, who have a queue.

That's the part nobody mentions when they sell you connectivity. Carrier APIs change all the time and without much warning, so a system built on direct links is only as stable as the last update nobody told you about. Each one reaches you as downtime first and a maintenance invoice second.

The real question is who owns the mess. Carrier data is inconsistent and badly documented and always will be, so someone has to sit in the middle and make sense of it. Either that falls on your operations budget every quarter, or the core platform does it for you.

That's what tigerlab's BMS is built around. A normalization engine sits between the carrier's backend and the work your team actually does, standardising the data as it arrives, so when a carrier reworks their schema the change gets handled at that layer instead of cascading into your quoting and underwriting. The messy data stays the engine's problem. It doesn't become yours.

27/07/2026

July wrapped up in the best way possible! 🎉

FIFA prediction champs walked away with cash prizes 💰⚽, our newbie and birthday babies came through with some delicious briyani, the famous pandan cake, and spaghetti. Plenty of chatter and laughter, this was exactly the break we needed from the daily grind at tigerlab.

27/07/2026

July wrapped up in the best way possible! 🎉

FIFA prediction champs walked away with cash prizes 💰⚽, our newbie and birthday babies came through with some delicious briyani, the famous pandan cake, and spaghetti. Plenty of chatter and laughter, this was exactly the break we needed from the daily grind at tigerlab.

24/07/2026

Some people watch football for the love of the game. But we guess Ali watched it for the cash prize, and honestly, RESPECT 🙌🏻

Congrats to our champion Ali, runner-up Melanie, who came painfully close to the big prize money, and Raidi, whose exact score predictions have raised serious questions in the office. Either he’s psychic, or he hasn’t seen his bed since FIFA kickoff. Possibly both.

Congratulations to all the winners, and stay tuned for more competitions and more chances to bag some cash.

P.S That’s Raidi in the reel, not Ali 😂

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