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Sohail Kasmani

Sohail Kasmani. Brand and marketing strategist in London: pharma brand management at Cipla and Alembic, now marketing strategy and AI adoption at ACTAsia. MBA, Brunel University London.

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Pricing an FDA-cleared surgical AI platform for Axial3D

  • Organisation : Axial3D (AXCEL platform)
  • Role : Four-person Brunel MBA team
  • Period : 2026
The AXCEL pricing tool

The problem

AXCEL, Axial3D’s surgical AI platform, sold for anywhere between $5 and $395 a case. Prices were set deal by deal, so every quote ended up on a manager’s desk. And customers were not priced by what the software was worth to them: a company selling $30,000 heart valves paid about the same per case as one selling $4,000 knee implants.

What we did

  • Benchmarked per-case prices of comparable surgical AI tools. Even at its highest price, AXCEL charged less than the cheapest comparable tool we found (around $750); HeartFlow is reimbursed at $1,017.
  • Valued AXCEL by specialty. The device it supports costs about seven times more in cardiac than in orthopaedics.
  • Proposed a three-part price: a yearly platform fee ($25K–$150K), a per-case price tiered by volume and specialty ($100 falling to $50 in ortho, $400 falling to $200 in cardiac), and a one-off setup fee ($30K–$100K).
  • Built a quoting tool so a sales rep can price a deal from five to seven inputs, with a one-page proposal and warning flags.
  • Built an 11-tab margin tool so the CFO can see cost per case, margin by deal, the effect of cost changes and what discounts really cost.

What the numbers showed

  • A 10% discount wipes out about 80% of the profit on a deal.
  • A mid-size cardiac deal earns an 82% margin; the biggest ortho deal earns 18%, and 4% if cloud costs triple.
  • Axial3D’s largest customer gets an estimated $7.1M of value and pays $720K, about 10%.
  • Run live, a mid-market ortho deal quotes at $300K and auto-approves at a 69% margin in under a minute.

What still needs checking

The per-case prices and the $25-a-case cost floor rest on benchmarks and cloud estimates. The next step is to test them against Axial3D’s own won and lost deals and real cost data.