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The shape of a
good decision.

We design how teams price, source, plan capacity, and allocate capital. The systems we build let them act on the full spread of outcomes.

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AI works best as a boost to a well-run operation, not as a shortcut past unclear data or missing structure. We start from the way your team already works, and we measure success the way you would: fewer surprises, hours won back, and bids priced with confidence.

How we work through a problem

Plan for a range, not a number

low likely high
The future is a range of outcomes, not a single forecast. We size plans to the realistic best, worst, and likely case.

Plan for a range, not a number

A single-number forecast hides the risk that matters. We model outcomes as full distributions, so plans are sized to the P10 and P90 rather than the average, and the worst case becomes a design input instead of a surprise.

See every option before choosing

act wait
Act now, wait, or commit in stages? We map where each path leads, so options are compared instead of guessed.

See every option before choosing

Most operational choices hide options: wait for better information, hedge, commit in stages. Drawing the tree, with probabilities and payoffs attached, turns a debate of opinions into a comparison of branches.

Know what's worth finding out

value of knowing cost of finding out
More research is not always worth it. We check what an answer would be worth before paying for it.

Know what's worth finding out

Every signal has a price: a report, a pilot, a month of waiting. We estimate what a piece of information could change before buying it, so analysis stops when it stops paying for itself.

Focus where it matters

demand price lead time labor cost capacity small effect big effect
A few factors drive most of the outcome. We find them, and put the effort there.

Focus where it matters

Sensitivity analysis ranks the inputs that actually move the decision. The wide bars earn real modeling attention; the narrow ones get a documented assumption and no more.

Where we can help

Processes that are repeated, instrumented, and consequential: the routine loops where most operating cost lives. Six examples. The scope of an engagement is set together.

€/quote

Sales, pricing

Bid quality, win-rate calibration, margin floors. Fewer ad-hoc discounts, more priced exposure.

variance

Procurement

Supplier selection under uncertainty, with total-cost models that include lead-time risk and quality variance.

P10–P90

Forecasting

Demand and capacity as full distributions. Plans sized to the spread, with a deliberate worst-case.

h/wk

Supply chain

Routing and prioritization under capacity constraints, planned against real lead-time variance.

min/case

Customer service

Triage, prioritization, exception handling. Faster routing of the cases that actually need a human.

σ planning

Finance

Forecast review, scenario sizing, capital allocation. Distribution-aware planning with explicit trade-offs.

Two ways to work together

AI capability uplift

We train your teams to build custom AI workflows: identifying value-adders, surfacing relevant information, integrating tools deeply into existing software, and governing autonomous agents.

12 weeks. Ends with a working system and a team that owns it.

Operational software in development

We are building software for specific industries and operations, designed to plug into existing tools and data and solve a clear, measurable problem very well. First releases targeted for late 2026.

Pilot partnerships. 2 to 4 design partners per product.

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Who you'll be working with

Our backgrounds are in decision analysis, operations research, and AI, and in running the kinds of operating teams we now build for.

Our work focuses on integrating AI into the processes where it materially shifts outcomes. We also help clients apply modern mathematical modelling to sharpen strategy and operations.

Base
Helsinki, FI
Founded
2025
Fields
Mathematics, AI
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