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How Sensible enables internal teams to solve tickets 15x faster and better manage climate risk


Sensible Weather, a climate risk technology company, was scaling rapidly on the heels of raising a $12M Series A. Utilizing just a single engineer, Sensible adopted the Retool platform to streamline operations across internal teams—from product, to business development, to support. 

We trace how this engineer single-handedly integrated with internal databases and external tools–like Zendesk and Stripe–to scale workflows and enable teams to solve tickets ~15x faster.

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Expanding weather products, fragmented workflows

Sensible partners with outdoor travel booking platforms to sell Weather Guarantees during the checkout process. These guarantees reimburse customers for inclement weather experienced on their trip.

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Enabling a seamless experience for Sensible’s booking partners and their customers involved juggling a number of variables internally—from partner integrations, to weather forecasts, to trip reimbursements, to comms across SMS and other platforms.

As the product expanded to offer new weather features, the support team had to handle new types of inquiries which required querying databases and making ad-hoc API requests.

As new booking partners were onboarded, product and biz dev teams had challenges understanding how far along partners were in the Sensible integration process—were they in production, or still in testing? And it took even more lift from engineering to configure these integrations.

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Searching for an integrated solution

Mark Bedanov-Pack, a software engineer at Sensible, recognized how painful it was for these internal teams to handle inquiries. “These processes can be error-prone and overall take a lot of time for our teams.” Mark noted that data silos were only increasing, along with the amount of tribal knowledge stored away in channels and internal comms.

Mark searched for a solution that connected with Sensible’s tech stack, and fit into the workflow of internal teams. He landed on Retool because it fit his search criteria across four key dimensions:

  1. Integrations: Retool would enable Mark to quickly iterate on support and admin-related features by integrating with both internal APIs and key external ones such as Zendesk to pull tickets, and Stripe to pull transactions.

  2. Pre-built UI library: Retool came with a library of pre-made UI components ready to drag and drop into internal apps. And updates could be pushed fast: “Engineering could make UI changes and push a new release of our customer support app in minutes, instead of having a team of dedicated frontend and backend engineers for this app.”

  3. Authentication: Retool allows for multiple types of authentication like Basic Auth, OAuth 2.0, Auth0, so we could use the authentication pattern that we deem appropriate and secure.

  4. Security & Permissions: Retool would enable engineering to set up safeguards for new customer support agents to view and modify data objects or make API calls, without the risk of making unintentional changes. Combined with access and permissioning, “only specific people could perform an action which would be key as our customer support team grows and people have different responsibilities.”

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Integrating Retool into the tech stack

When it came time to implement Retool, the integration process was fairly straightforward:

  1. Setup permissions and auth (Basic Auth, OAuth 2.0, Auth0) to hit services.

  2. Go into the Retool UI and configure resources.

  3. Integrate internal APIs (manage Weather Guarantee objects, pull coverage details, etc.) and external APIs (for services like Zendesk and Stripe).

  4. Test in dev and setup connectivity to production environments.

  5. Start developing Retool apps!

Even though Mark was a team-of-one, these initial steps took less than three days, which was “super satisfying, since connecting different data sources and services can be one of the pain points during software development”.

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Layering a UI on top of Weather Guarantee data objects

With the foundation set, Mark went to work on the UI. He took advantage of Retool’s library of pre-made components—from data tables, to key-value objects, and the various input fields found in a widely used frontend library. These UI building blocks enabled Mark to shape apps in a way that best suited the internal workflow challenges at hand.

“A lot of our data objects are best represented in a table structure, where a row can represent a Weather Guarantee. We can then take that row object and perform any other visualizations or modifications needed to assist a customer. This includes viewing coverage for individual days, customer communication preferences, and more.” Mark Bedanov-Pack, Software Engineer, Sensible

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Layering in the necessary UI components and plumbing to API endpoints that needed to be invoked only took a few days. For Mark, “this saved a ton of engineering time, as a similar application built from scratch would have taken months to develop.”

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Consolidating support workflows into one internal app

Once the data was piped in, the endpoints connected, and the UI layered on top, Mark’s internal app (codenamed: Nimbus) was ready for customer support agents.

The first support workflow to tackle centered around trip reimbursements. While these reimbursements were often automated, occasionally the support team had to manually look up a database record, validate the weather forecast, and then notify eligible customers via SMS. With Nimbus, agents could pull dozens of Weather Guarantees directly into table views, pull weather data to take a closer look at what customers experienced on the trip, and trigger SMS notifications detailing reimbursement information.

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The majority of the customer support workflow, from viewing open Zendesk tickets to issuing payouts, could now happen inside one internal app. That meant less cognitive load from switching apps and learning different tools which had their own interfaces and workflows.

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With Nimbus deployed, support agents solved tickets ~15x faster.“A lot of the customer support processes that took 10-30 minutes per ticket for our support team, now take a single minute or two.” And Mark noticed there were fewer concerns about scaling the support team in general. “Overall, the internal apps built with Retool have given us the confidence in growing the customer support team and onboarding new agents, just knowing that we can accommodate our customers’ needs at a much faster rate than before.”

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Building dashboards for product and biz dev teams

Nimbus also automated partnership management for Sensible’s product and biz dev teams. These teams worked with partners like Liftopia–a platform to book lift tickets at resorts around the world–to embed Weather Guarantees in the checkout process.

Dashboards in Nimbus enabled product and biz dev teams to view the various partners, coverage configurations, and whether Weather Guarantees were shipped to production or still being tested in a sandbox environment.

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Dev environments could be activated or deactivated depending where a partner stood in the onboarding process. Instead of a constant back-and-forth on implementation, engineering teams at Sensible and their travel booking partners could focus on what mattered: building a great experience for end users.

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Results—and what's in the forecast

It took just a single engineer inside of a fast-growing startup to spin up Retool and streamline internal operations.

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“After we've integrated with Retool, we now have a lot of these applications and dashboards with automated workflows, and it's really helped accelerate these processes for our customer support, product, and business development teams, and the customers that are buying these Weather Guarantees.”  — Mark Bedanov-Pack, Software Engineer, Sensible

As Sensible’s Weather Guarantee launches in international markets, Mark finds himself in a position to scale internal tools as quickly as the product scales. Sensible plans to embed deeper weather analysis and support for new types of communication and reimbursement in Nimbus to accompany their global rollout.

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