P2Predict
This parametric pricing tool for procurement and sales learns from a company's purchase history which factors actually drive a part's price (supplier, material, spec, region), and lets an AI agent ask whether a quote is fair, returning a price estimate with a confidence range and a spec-by-spec breakdown. Use cases include data-driven negotiation targets, engineering value workshops (estimating BOM savings from spec changes), and sales bid preparation. It runs as a CLI, ships an MCP server so it plugs into Claude, GPT, or other agent harnesses, and works 100% locally and privately; it is free for internal company use and source-available. The author also validated its math on public TDC ADMET pharma benchmarks (placing 7th of 24 on one board) and used it to predict rent savings when moving apartments.
What it addresses
Price quotes and negotiation targets are often guesses; buyers and sellers lack data on what actually drives a part's price.
Shared over time
Each entry reflects what was shared on that date. Details may have changed since then.
P2Predict
This parametric pricing tool for procurement and sales learns from a company's purchase history which factors actually drive a part's price (supplier, material, spec, region), and lets an AI agent ask whether a quote is fair, returning a price estimate with a confidence range and a spec-by-spec breakdown. Use cases include data-driven negotiation targets, engineering value workshops (estimating BOM savings from spec changes), and sales bid preparation. It runs as a CLI, ships an MCP server so it plugs into Claude, GPT, or other agent harnesses, and works 100% locally and privately; it is free for internal company use and source-available. The author also validated its math on public TDC ADMET pharma benchmarks (placing 7th of 24 on one board) and used it to predict rent savings when moving apartments.
Problem: Price quotes and negotiation targets are often guesses; buyers and sellers lack data on what actually drives a part's price.
Audience: Procurement and sales teams, plus engineering teams running value workshops to cut BOM costs.
Posted by @ahmedkhafsi · Original comment ↗
“Working on P2Predict, a parametric pricing tool for agents, mainly in procurement, but also sales. Point it at your own purchase history and it learns what actually drives the price of a part (supplier, material, spec, region, whatever), then an AI agent can ask it things like "is this $14.20 quote fair" and get back a number with a confidence range and a spec-by-spec breakdown instead of a guess.”