What clients say
Feedback from planning teams who've used the tools
These are notes from real planning contexts — engineering leads, finance managers, and infrastructure teams who worked through AI cost planning with pyrelaneslane's tools.
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Zainal Abidin
Head of Infrastructure, Petaling Jaya
We'd been trying to build our own model for three months and kept hitting the same problem — nobody could agree on which assumptions were in scope. The pyrelaneslane template gave us a shared starting point and the conversation shifted from arguing about figures to actually discussing what we wanted to plan for.
May 2025 — Cost Model Template
Nurul Liyana
Finance Manager, Kuala Lumpur
Finance and engineering were working from completely different numbers going into our annual budget cycle. The Scenario Toolkit gave us one file that both teams could update. It didn't solve every disagreement but it at least meant we were disagreeing about the right things.
April 2025 — Scenario Toolkit
Koh Chee Wai
Senior Engineer, Cyberjaya
The usage guide is genuinely useful — I've handed the template to two colleagues who hadn't seen it before and they were both up to speed within an afternoon. That kind of self-documentation is rare in planning tools and saves a lot of back-and-forth explaining.
May 2025 — Cost Model Template
Siti Rahimah
Operations Lead, Shah Alam
The bespoke build took longer than I expected to kick off — the discovery session needed two rounds to nail down the planning question precisely. But the end result was genuinely specific to our situation, not just a renamed generic template. Worth the time investment.
March 2025 — Bespoke Model Build
Faizal Ibrahim
Data Engineering Manager, KLCC
The comparison table in the Scenario Toolkit is the one feature I keep coming back to. Being able to drop three different on-premises versus cloud configurations side by side and see the cost difference without manually building a separate view each time saves real hours in planning cycles.
April 2025 — Scenario Toolkit
Tan Mei Ling
Planning Analyst, Bangsar
I appreciated that the handover session for the bespoke model was structured around what our team needed to maintain the model going forward, not just a walkthrough of what had been built. We left the session confident we could update it independently.
May 2025 — Bespoke Model Build
Planning contexts in detail
Three examples of how different teams approached AI infrastructure cost planning with pyrelaneslane tools.
Planning Challenge
A Kuala Lumpur-based technology firm needed to prepare a multi-year budget for GPU compute and storage for a new inference service. Their existing spreadsheet didn't separate compute cost from storage cost, making it hard to model different utilisation scenarios independently.
How pyrelaneslane Helped
The Cost Model Template provided separate layers for compute, storage, and networking with named assumptions for each. The team ran three scenarios — baseline, peak load, and scale-down — using the worked examples as a starting structure.
Outcome
The planning team presented a three-scenario cost range to the board within two weeks. The assumption documentation meant the finance team could review the model without requiring a separate briefing session.
Timeline: 2 weeks — Cost Model Template
Planning Challenge
A regional logistics company with a data engineering team in Shah Alam was preparing a proposal comparing on-premises GPU servers against a managed cloud AI service. Finance and engineering were working from different cost figures with no reconciliation process.
How pyrelaneslane Helped
The Scenario Toolkit gave both teams shared access to the same model. They built separate scenarios for on-premises and cloud configurations and compared them using the built-in table. Finance could update pricing assumptions; engineering could update utilisation estimates.
Outcome
The proposal was completed in three weeks. The team exported the comparison table and used it directly in their internal presentation. The shared model reduced the number of rounds of reconciliation from five to one.
Timeline: 3 weeks — Scenario Toolkit
Planning Challenge
A financial services organisation in Kuala Lumpur needed to model AI infrastructure costs for a new compliance-related workload. Their existing cost allocation methodology treated AI compute differently from standard server costs, making standard templates unsuitable.
How pyrelaneslane Helped
The bespoke model build started with a discovery session to map the organisation's specific allocation methodology. The resulting model integrated their internal cost centre structure and produced outputs compatible with their existing budget reporting format.
Outcome
The model was delivered in four weeks and handed over in a structured session. The planning team was able to update the model for the next budget cycle without external support. The model has since been adapted for two additional workloads.
Timeline: 4 weeks — Bespoke Model Build
Get in touch
Phone
+60 12-408 5271Address
Jalan Kia Peng 33, 50450 Kuala LumpurWorking Hours
Mon–Fri 9:00 AM – 6:00 PM (MYT)
Trust indicators
80+
Teams using pyrelaneslane tools
4.7
Average rating from clients
3+
Years of delivery experience
12
Bespoke builds completed
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