Customer Story: Pantera Has Changed the Way We Work

Background

Avison Young is one of the UK's leading commercial real estate advisory firms, and its capital markets business is one of the fastest growing parts of the firm, expanding through a run of senior hires as it builds out its UK platform. Sam Hume-Kendall is an associate director in the capital markets investment team, working across acquisitions and disposals. He has been using Pantera for nine months.

The Challenge

Before Pantera, the team used a combination of legacy providers and custom-built Excel spreadsheets for modelling. The legacy provider handled standard commercial investment appraisals reasonably well, but when deals got complex, the platform's rigidity forced the team back to Excel.

When it came to renewal conversations and the pricing changed significantly, the economics stopped making sense and the team started looking for an alternative. Excel was reliable, but slow. Modelling often sat with one or two people on the team, not because others couldn't do it, but because of the time it took. Senior agents would often scope modelling out rather than run it themselves as their time is better spent in front of clients than doing Excel admin. And with manual tenancy schedule input, the volume and complexity of commercial leases created the need for time-consuming internal checks before anything could go to a client.

Setting up a model, even before it got to producing coherent outputs, took around an hour. Sensitivity analysis was one-dimensional and comparing scenarios meant switching between separate spreadsheets.

Why Pantera

The team's initial response to Pantera was the interface itself. Rather than a traditional spreadsheet, the platform surfaces the logic of the model visually, making it easier for clients to engage directly with the numbers.

“With Excel and our legacy provider it was an exercise in simplification. With Pantera it's an exercise in personification of the numbers. You can see not just the output, but precisely how it's been reached.”

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The asset strategy visualisation page, which maps income streams across the hold period, became an immediate hit internally. Clients could read it without explanation. The customisable exit page, which lets users show only the return metrics relevant to a specific client, removed the clutter that came with the legacy provider's fixed outputs.

Responsiveness from the Pantera team during onboarding also stood out. Customisation requests, whether straightforward or complex, were turned around within days, not months.

The Results

From an hour to under a minute

Building a model to the point of a coherent output used to take around an hour. With Pantera, AI does the heavy lifting, populating the tenancy schedule and core inputs in under a minute. The agent takes it from there, so a complete appraisal ready to send to a client is finished in under ten minutes. The speed comes from the AI, but control stays with the agent. Every input is visible and adjustable, rather than hidden inside a black box no one can see or control. The team was cautious about trusting AI-extracted lease data at first. Confidence came quickly, because Pantera's AI is built specifically for real estate, with guard rails that understand how commercial leases behave rather than a general model guessing at them. Extracting tenancy schedules this way is now standard practice.

Built to scale a growing team

The hour saved on each model compounds across a growing team. New joiners are productive from day one rather than spending weeks learning a rigid legacy system. Senior agents run their own appraisals in ten minutes rather than scoping them out, so senior time goes back to clients and winning mandates. For less experienced team members, AI data population captures the lease detail that is easy to overlook at volume, such as break options, fixed uplifts and review structures, so the model is complete before anyone looks at the numbers. As the team grows, modelling capacity scales with it rather than becoming the bottleneck.

“Within two or three models you're completely across it. After that, the time you put in at the start is a drop in the ocean compared to what you get back.”

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Responsive product development

When the team needed something that was not already in the platform, the turnaround from request to delivery was days, not months. Customisations were either built immediately or scoped and delivered shortly after, regardless of complexity. Rather than working around the limitations of a rigid system, the team could flag what they needed and have it built in.

“It was never more than a week from idea to inception to delivery, even if it was something complex. Instead of us having to go away and build it, the team on the ground were able to build it into the Pantera platform. It has helped us open up our workstream.”

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Scenario comparison

The clone and compare function solved one of the most persistent frustrations with previous platforms. Comparing two sets of numbers no longer requires switching between spreadsheets. Multiple business plans, asset management strategies, exit periods, and hold periods can be layered up and compared in one view.

“The design has clearly been led by someone who has been in the position of an agent. This is something I love using with clients.”

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Multi-output sensitivity analysis

Pantera's sensitivity analysis can display multiple output metrics simultaneously against two input variables, such as exit yield and acquisition price. Where every previous platform produced a single output per analysis, Pantera lets you choose; ungeared IRR, geared IRR, development yield, and equity multiple in one table. This has become a direct input for IC papers.

“You can do a full sensitivity analysis not just across one output but across your whole appraisal in one click. You can just plonk it on an IC paper and say: there it is.”

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What's Next

THE STORY IS STILL BEING WRITTEN

Cross-team intelligence

As Avison Young's capital markets teams have moved to a unified fee pool, Pantera's shared platform has surfaced deal intelligence across the wider organisation.

Previously, a team in London and a team in Manchester working for the same client would have had no visibility of each other's work. Now when you pull up the map page and see every asset we're underwriting across the UK, labelled by client, you start to see patterns in risk appetite that you'd never have spotted otherwise. It gives us a genuinely interesting insight into how client appetite shifts depending on where they're investing. That's something we couldn't see before.

“That kind of visibility across a team is a byproduct of normal deal flow on a shared platform. It was not possible before.”

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‍Building a proprietary comps database

Looking forward, Avison Young's team has already been capturing valuable investment and leasing comps data in Pantera. Over time, this will allow direct comparison between how buildings have been valued and how they have traded, creating an internal comps database the firm owns and controls.

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The AI layer, built in

What excites the team most is what is still to come. As AI tooling advances, those gains arrive inside a platform already built for real estate, with nothing for Avison Young to build, integrate or maintain. The team simply gets the benefit as part of the product, so their time stays on winning mandates and fee earning work rather than on building or managing tools of their own. The Pantera team's pace of updates means the platform keeps improving underneath them while they stay focused on clients.

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‍In Sam's Words

“It's changed the way we work. We can model complex deals and compare scenarios in minutes, and it's given even our most experienced people new ways to communicate a deal to clients.”

“It caters for all skill sets, at any level. No matter how basic or intricate the numbers need to be, everyone on the team can put it together.”

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