Price to Win — Without Leaving Margin Behind

SpikeCore AI analyses historical award data, market benchmarks, and competitor pricing patterns to give you a data-backed pricing range for every bid. Stop guessing. Start winning on price.

Analyse Your Next Bid Price
THE PROBLEM

Pricing Blind Costs You Either Way

1

Over-priced bids lose on evaluation — you invest weeks of effort only to be disqualified on the financial score, often by a margin you could easily have closed.

2

Under-priced bids win contracts but destroy margin — winning at the wrong price is sometimes worse than losing, especially on multi-year government contracts.

3

Pricing decisions are made in a vacuum: teams rarely have access to what competitors are pricing, what the budget holder expects, or what similar contracts have actually been awarded at.

4

In markets with public award data (GeM, GEM, CPPP, SAM.gov, Contracts Finder), this information exists — but nobody has time to mine it systematically before submission day.

HOW IT WORKS

How Price Intelligence Works

1

Award Data Mining

SpikeCore AI continuously ingests public award notices from government procurement portals — extracting contract values, scope descriptions, winning bidders, and award dates.

2

Comparable Selection

When you upload an RFP, the system identifies the most comparable historical awards by scope similarity, sector, geography, contract duration, and buyer type.

3

Pricing Range Analysis

Award values from comparable contracts are normalised and benchmarked to produce a pricing range: the floor (minimum competitive price), the target zone (highest win-probability range), and the ceiling (estimated budget).

4

Competitor Signal Detection

Where public data reveals which competitors won similar contracts and at what values, the system surfaces these signals to inform your positioning strategy.

Key Benefits

Benchmark your price against real award data before you submit

Identify the highest price that still wins — protecting your margin

Detect competitor pricing patterns from historical award notices

Reduce the risk of disqualification on financial evaluation criteria

Available for Indian government tenders (GeM, CPPP) and US federal contracts (SAM.gov)

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