defft.ai
defft.ai provides a mobile recommendation engine that helps packaging sales representatives turn warehouse-floor observations into quantified operational proposals, reframing customer bids beyond unit price. The system captures photos, videos, and dictation during facility visits, then models cost composition across labor, storage footprint, and transit damage to demonstrate net operational advantage. Its interactive sliders let sellers adjust assumptions and show cumulative 12-month impact, with each interaction improving future recommendations.
- Sales Technology
- Artificial Intelligence
- Data & Analytics
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Packaging sellers are trapped in a "nickel game" where customers push for ever-lower unit prices, forcing sales teams to discount commodities rather than sell operational value. This narrow focus on unit price leaves significant cost savings on the table—material handling, storage footprint, and transit damage often dwarf the carton price itself, but sellers lack the tools to quantify and present those broader improvements.
Solution
defft.ai provides a recommendation engine that turns warehouse-floor observations into quantified operational proposals for packaging bids. Sales reps use the mobile app to capture facility evidence—photos, videos, dictation, and notes—during customer visits. The system then models the full cost composition, showing that unit price is often only a fraction of total operating cost, and generates a recommendation that reframes the bid around measurable improvements in pack-line labor, cube and footprint reduction, and transit damage. Each customer interaction feeds back into the system, making the next seller's recommendations smarter and more effective.
Target Audience
Primary users are commercial field sales representatives and account managers in the packaging industry, particularly those selling corrugated, containers, and related materials into manufacturing and distribution facilities.
Features
- Mobile application with camera, photo library, and microphone permissions to capture visit evidence including photos, videos, dictated notes, and audio directly into business records
- Cost-composition modeling that breaks down unit price versus modeled operating cost across a 12-month view
- Interactive sliders that let sellers adjust assumptions on pack-line labor reduction, cube and footprint reduction, and transit damage reduction to show net operational advantage
- Multi-dimensional tracking and data model connecting field evidence to quantified recommendations
- Account, territory, and meeting organization capabilities for field activity management
- Recommendation engine that improves over time as customer interactions accumulate