HAAS Alert Success Story

How HAAS Alert got the whole organization looking at the numbers with Aleph

With Marcel Chidoba, CFO at HAAS Alert

HAAS Alert operates Safety Cloud, the world’s largest real-time vehicle-to-everything (V2X) network, connecting thousands of emergency and roadway fleets with 3 million passenger vehicles through navigation apps and in-vehicle systems.

Behind that reach is a complex business spanning first responders, utilities, construction teams, transportation agencies, and global automakers. Each segment brings its own revenue and cash-flow dynamics, requiring a finance system flexible enough to reflect how the business actually operates.

Its previous web-based platform constrained the forecasting model and made reliable reporting harder with intermittent data refreshes.

Returning to standalone spreadsheets would solve the flexibility problem, but sacrifice the automation, consistency, and organization-wide access the team needed.

I mean, I think the big headline for us is people are actually looking at the numbers now. And I mean that in a way of, like, across the organization. We've been able to really automate reporting, and we're spending a lot more time using the information as opposed to preparing the information. I'm Marcel Chidoba, I'm the CFO at Haas Alert. We're a connected vehicle platform delivering real time hazard alerts to drivers on the road. We sell our solution called Safety Cloud to first responder fleets, utility construction, DOT agencies, and we also deliver a software solution to automotive OEMs. Having flexibility was absolutely paramount, and we ran into that challenge when we were locked into kind of a web based platform. The second big thing that made me want to look for a switch was that we were faced with constant interruptions on data refreshes and just data availability and the poll consistency was was intermittent. Whereas here, can take out reams of data, takes me seconds, and I can put that in a automated refresh repository that drives a sales dashboard in Google Sheets or in a dashboard or in Aleph. The gaps that we had before have been eliminated or closed. And, you know, one of them was consistency and availability of reporting. You spend a lot of time doing, you know, reporting to, you know, thirty plus different stakeholders, but specifically to to board and investors, consistency is key. So being able to produce data and structure it in Aleph such that it meets the output that I need for them in a simple dashboard, I think that's a big ROI whether you see it or not. The other one I mentioned was just time of getting stuff done. I mean, things are flowing faster. I'm not complaining as much about needing to add a bunch more analysts to the team. And and also, I mentioned earlier just the quality and speed of working with the system and reliance on numbers. You know, my happiness factor has gone up a little bit. Today, we're heavily using the chatbot, the MCP connector, and what those do for us is it allows users that use Aleph to quickly go in and ask questions. And those questions would previously take up the time of an analyst or a finance manager or an accountant or the CFO. And some of them are just one liners in Slack. And why do you need to wait for me to respond when you can just get the answer directly? And so that's been a really nice feature. Also just a lot of analysis. I mean, the BVA as well as, I think I did one earlier today on sales tax jurisdictions. This stuff comes really easily when you have AI working for you. The team did a fantastic job getting us connected, onboarded, and that those steps were super easy. We were live with Aleph and, you know, definitely under the two week window, that I think we were kinda trying to target. But I wasn't just here. I'm here for onboarding. We've had regular check ins from the Aleph team, making sure, you know, everything's going well or questions on features. And I think every conversation, I I get introduced some to something new that I should dig a little deeper from the tip of the iceberg, and we do, and it turns out to be another good feature. Ultimately, you need to have a reliable database where everything comes from. And for us, that became kind of a left at the center as a source of truth of where to pull information for and where to upload it and where to modify it. If you don't have that ground, base of where everything comes from, it can get messy fast and people are looking at different things. And so I think having a core sort of database, which ideally is your forecasting reporting system, is essential, and I don't believe that'll go away. Then you'll have a variety of kind of sprawling AI tools around it that companies will create to suit their needs. I'd say Aleph is an excellent solution for finance teams that want their forecast model in Excel, but want to have the automation of a platform tool, being able to harness data from numerous sources and then really automate that. And the kicker is everything is kind of AI powered and becoming more so natively to Aleph. So I think there's a lot of best of both worlds that we gain from it. And I think that's what I think finance teams should take a look at.

Challenges before Aleph:

Rigid forecasting: HAAS Alert's finance team needed to model different revenue streams and cash-flow behaviors across multiple go-to-market segments. A locked web-based platform could not provide the flexibility Marcel had in Excel.
Unreliable access to data: Data refreshes were frequently interrupted, and pulls were inconsistent. That made availability a concern for a team that needed reporting on demand.
Too much preparation: Finance spent too much time extracting, restructuring, and preparing data before anyone could use it.
Different views for different stakeholders: Reporting had to serve more than 30 stakeholders, including department leaders, the board, and investors. Adapting outputs after the fact added work and made consistency harder to maintain.

Having flexibility was absolutely paramount. We ran into that challenge when we were locked into a web-based platform.

Marcel Chidoba

CFO

The solution and results after Aleph:

HAAS Alert chose Aleph to keep the modeling flexibility of Excel while adding a connected platform for automation, reporting, and analysis:

Excel flexibility with a platform behind it: The finance team can build a customized forecasting model in Excel, then upload its outputs to Aleph alongside live data from ERP, CRM, revenue, production, and marketing systems.
Consistent, usable data: SQL-built tables and shared mappings give the team control over how data is parsed, classified, and presented. Instead of exposing every available field, HAAS Alert can shape each dataset around the information people actually need.
Reporting that stays on: Instant data pulls feed recurring dashboards in Google Sheets and Aleph. Finance can distribute always-on reporting and push regular updates through Slack instead of rebuilding each view from scratch.
Answers at the point of need: Drill-downs let Marcel inspect the detail behind a number and answer questions during a meeting. Aleph's chatbot and MCP connector also give users a direct way to ask questions that once had to wait for an analyst, accountant, finance manager, or CFO.
A fast start with continued support: HAAS Alert was live with Aleph in under two weeks. Regular check-ins have continued beyond onboarding, helping the team discover and adopt more of the platform over time.

Today, we're heavily using the chatbot and MCP connector. People can quickly ask questions that would previously take up an analyst's, finance manager's, accountant's, or CFO's time. Why wait for me when you can get the answer directly?

Marcel Chidoba

CFO

The Impact

With financial data flowing through one flexible, trusted environment, HAAS Alert's finance team has shifted its time from preparing information to helping the organization use it:

More people using the numbers: Always-on dashboards, Slack updates, and self-serve questions make financial information available across the organization, not only inside finance.
More consistent reporting: Finance can structure board, investor, and internal reporting around the views each audience needs while keeping the underlying data and calculations consistent.
Faster work without equivalent team growth: Marcel says work is flowing faster and the pressure to add more analysts has eased, even as the team supports a broad set of stakeholders and questions.
Greater confidence in every answer: Instant pulls and drill-downs make it easier to understand how a number was constructed, inspect the detail behind it, and explain it clearly.
A trusted foundation for AI: Aleph serves as the central source for pulling, uploading, and modifying financial information. That gives HAAS Alert a governed foundation for using AI without letting different teams create conflicting versions of the same metric.

The big headline for us is people are actually looking at the numbers now, across the organization. We've automated reporting, and we're spending a lot more time using the information instead of preparing it.

Marcel Chidoba

CFO

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