Sales, pricing
Bid quality, win-rate calibration, margin floors. Fewer ad-hoc discounts, more priced exposure.
We design how teams price, source, plan capacity, and allocate capital. The systems we build let them act on the full spread of outcomes.
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.
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.
Bid quality, win-rate calibration, margin floors. Fewer ad-hoc discounts, more priced exposure.
Supplier selection under uncertainty, with total-cost models that include lead-time risk and quality variance.
Demand and capacity as full distributions. Plans sized to the spread, with a deliberate worst-case.
Routing and prioritization under capacity constraints, planned against real lead-time variance.
Triage, prioritization, exception handling. Faster routing of the cases that actually need a human.
Forecast review, scenario sizing, capital allocation. Distribution-aware planning with explicit trade-offs.
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.
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.
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.