Antelope Success Story

How Antelope multiplied the impact of its lean finance team with Aleph

With Alex Almy, Director of FP&A at Antelope

Antelope is a family of pet care brands backed by Alpine Investors, focused on making high-quality, trusted products more accessible to pet parents.

Across its four brands, the company manages roughly 600 SKUs sold through 16 channels, creating thousands of combinations for its lean finance team to forecast, budget, and report on.

Before Aleph, that work depended almost entirely on Excel and manual exports from NetSuite. Reports could take hours to run or time out altogether. Updating Antelope’s 100-tab monthly board reporting workbook meant pulling and stitching together as many as 20 CSVs—and repeating the process whenever a late adjustment came through.

With Aleph, Antelope connected NetSuite and had usable data within hours. The finance team went live a full month ahead of its internal target, instantly shaving days off their routine reporting and forecasting work and creating more capacity to help drive decisions across the business.

Implementation was both fast, and we're using it very quickly. And it was, like, one of those things where you're, like, didn't trust that it was working so well because you were like, this can't be working so well, but it was. Name is Alex Almy, director of FP&A here at Antelope. We are a platform that invests in pet brands, and so we are responsible for all forecasting, budgeting, and a kind of regular reporting that goes along with that. We essentially were, I would call it, in the stone age using just Excel, so we had no other software tooling. We use NetSuite for our ERP, but for us as the end user, kind of the reporting aspect of it is terrible. Take you just hours to pull this data out sometimes. We wanna be more than just, like, reporting out on the on the news. We kinda wanna help drive the conversation. The ease of just getting that data, just improved, like, you know, a 1000x kinda thing. And then the other piece of it, which I really liked, is given we're kind of a small team, we don't have kind of a lot of, you know, IT or systems folks, like, in-house. I wanted it to be self-serve. So, what I loved about Aleph is a lot of the stuff on the back end, you know, within the data tables and whatnot, you can kind of choose your own adventure and you can kind of manipulate it a little bit how you wanna do things and how you wanna see the data and and augment it a certain way, and it's it's just very intuitive for us. And then last but not least, being able to use both Excel and Google Sheets. It's kind of a funny thing, but I would say about eighty percent of our org operates on Google Sheet land. And so we in finance are like Excel junkies. And so being able to have a tool that can pass data between the two was super helpful. We had kind of goals to be using it for kind of our internal reporting by x date, and I think we exceeded that date by a full month. And I think we hooked it up at nine in the morning, and by by lunch, I had data that I could touch and feel. And we had a very similar experience with the actual implementation when we went live. I think it was even faster somehow. And what was very interesting to me was essentially when we flipped the switch, effectively the data was a hundred percent correct, which I was shocked because I was like, something's gotta flow through wrong or we've broken something on our end on NetSuite so it wouldn't flow into your world, but it just worked. I mean, the Claude MCP, I've just been, like, obsessed with recently. This customized layer of data, like, you know, an enterprise data warehouse essentially that you can control the org structure of, and then layering that in with something like Claude is just, like, super amazing for both kind of content creation, for lack of better terms. So able to produce presentations using the data in Aleph with Claude has been really impactful, and I hope to do more stuff like that and kinda using, you know, Aleph as a source of truth for our financials and Claude to kind of update commentary. And so I think you guys built a really good foundation with the system, and then it's, like, just right to use with something like Claude. I mean, the classic one is is time saved. Right? Because you can say, like, there's real dollars associated with that, I would say. The other side of the equation is, you know, how much are we able to do more now? I've noticed it, you know, just because we're able to be so much faster at things and deliver, you know, reports, answers to questions. You know, the business is asking more of us now, which is a great feeling. You know, it almost feels like untapped demand. It's like they didn't know what they could get essentially before, and the speed. And I think that is a great value because it makes us more of a partner to the business instead of just kind of being like, you know, scorekeepers for lack of better term. So it kind of it's hits two ways there. But that's less hard to quantify, and it's funny for a finance guy maybe to say that, but I think that, like, you know, subjective value add is very powerful. And I think we're seeing it in the pace of play in the business: being able to kind of work cross-functionally and answer questions and deliver, you know, answers to those questions so quickly has just been really great.

Challenges before Aleph:

Complexity multiplied across SKUs and channels: Forecasting at the SKU and channel level created more combinations than the existing Excel workflows could manage cleanly in a single process.
NetSuite built for accounting, not FP&A: NetSuite handled the back-end accounting well, but its native reporting was slow and limiting. Pulling a report the way the team needed it sometimes made the system time out entirely.
A reporting process vulnerable to rework: File size and formula complexity forced the team to divide workflows across spreadsheets. A late accounting entry could trigger another round of exports and updates.
A lean team that needed self-service: Without dedicated systems resources, Antelope needed finance tooling it could configure and maintain without relying on consultants or data engineers.

We wanted to be more than just reporting the news. We wanted to help drive the conversation. Now we have the capacity to be more proactive and work with the business.

Alex Almy

Director of FP&A

The solution after Aleph:

Antelope chose Aleph around three priorities: a dependable NetSuite integration, a self-serve data model, and the flexibility to work across Excel and Google Sheets.

NetSuite data structured for FP&A: Aleph brings Antelope’s custom fields and existing taxonomy into a connected environment the finance team can use for reporting and analysis.
Mappings finance can own: Alex can update rollups, classifications, and reporting views directly in Aleph, including different views for internal, sponsor, and lender reporting.
Spreadsheets stay part of the workflow: Finance can continue working in Excel while sharing refreshed data with the roughly 80% of the organization that operates primarily in Google Sheets.
Refresh instead of rebuild: When the underlying numbers change, the team can refresh the integration and pull the latest data into its spreadsheets without repeating every export.

We hooked it up at nine in the morning, and by lunch I had data that I could touch and feel. When we flipped the switch, the data was effectively 100% correct. Everything just works. The ease of getting the data improved 1,000x.

Alex Almy

Director of FP&A

The impact:

With less time spent preparing data, Antelope’s finance team can put more energy into understanding the business and helping others act on the numbers.

Reporting live a month ahead of schedule: The team adopted Aleph for its monthly reporting cycle earlier than planned because the implementation and data validation moved so quickly.
More consistent recurring reporting: Internal, board, sponsor, and lender reporting can all draw from the same structured financial data, formatted the way each audience wants to see it.
Faster answers across the business: Finance can respond to cross-functional questions much faster, increasing what they are able to support across the business
More capacity for forward-looking work: The team can devote more attention to forecasting, analysis, and helping business leaders understand what to do next.

The business is asking more of us now, which is a great feeling. It almost feels like untapped demand. The business didn’t know what they could get at this speed. It makes us more of a partner to the business instead of just being scorekeepers.

Alex Almy

Director of FP&A

The next layer: Building on the foundation with AI

With a trusted data foundation in place, Alex has started bringing AI into Antelope’s finance workflows through Aleph’s native AI capabilities and its MCP connector for Claude.

AI-assisted data structuring: Aleph suggests mappings and helps apply rules across large data tables, reducing manual work and keeping financial data clean, consistent, and ready for use.
A trusted financial fact checker: Before work goes out, Alex uses Claude with Aleph as a final set of eyes, checking that every number and its corresponding commentary trace back to Aleph as the source of truth.
Turning financial context into action: The MCP connector lets Claude work from the same structured financial context as the FP&A team, creating opportunities to explore performance, respond to questions, produce deliverables, and automate more work across the finance workflow.

Together, these capabilities help Antelope keep its data clean, increase confidence in every output, and turn trusted financial context into action—expanding FP&A’s reach and impact across the organization.

I’ve been obsessed with the Claude MCP recently. The customizable data layer provides an enterprise-grade data warehouse that we control, and then having the ability to layer that in with something like Claude is just super amazing.

Alex Almy

Director of FP&A

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