Co-Founder
Competera
The platform provides an AI/ML pricing engine for enterprise retailers that ingests ERP, sales, inventory and competitor price data to generate demand‑elasticity‑based price recommendations. It includes scenario simulation, a human‑in‑the‑loop rule layer, and automated omnichannel price updates, delivering real‑time dashboards and API integration for millions of SKUs under ISO 27001 security.
Updated 16 days ago
Funding
Raised to date
$3MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Funding rounds are not available yet.
Founders
Product
Problem
Enterprise retailers operating across online and physical channels often rely on manual pricing processes and fragmented competitive data, leading to inconsistent price execution, missed margin opportunities, and unpredictable revenue growth.
Solution
The platform delivers a contextual AI/ML pricing engine that ingests internal ERP, transaction, and inventory data alongside continuously crawled competitor pricing signals. By modeling over twenty demand drivers, it generates price recommendations that reflect true demand elasticity and forecast business impact for any scenario. Users can simulate pricing strategies before rollout, while a human‑in‑the‑loop rule layer ensures strategic oversight and compliance. The solution automates price updates across all sales channels, provides real‑time monitoring, and presents actionable insights through an enterprise dashboard. Built for large retailers, it scales to millions of SKUs and integrates via APIs with existing commerce, ERP, and BI systems, all under ISO 27001‑certified security.
Target Audience
The solution is aimed at enterprise retailers—both B2C and B2B—who manage large, multi‑channel assortments, including pricing managers, merchandising teams, and C‑level executives overseeing revenue and margin performance.
Features
- End‑to‑end data pipeline that extracts, cleans, and enriches ERP, sales, and cost data, then augments it with AI‑driven competitive price matching and web crawling
- Contextual AI models that evaluate >20 demand factors (seasonality, promotions, store traffic, competitor actions) to compute full demand elasticity with >95% forecast accuracy
- Scenario planning engine allowing users to simulate “what‑if” pricing changes and view projected margin, revenue, and volume impacts before deployment
- Human‑in‑the‑loop rule framework where pricing managers can apply business rules, thresholds, and approval workflows to AI recommendations
- Automated omnichannel price execution that pushes optimized prices to e‑commerce sites, POS systems, marketplaces, and mobile apps in real time
- Granular SKU‑level analytics dashboard with heat‑maps, contribution analysis, and alerts for price deviations or compliance breaches
- Scalable micro‑services architecture with REST/GraphQL APIs for seamless integration with existing retail tech stacks
- ISO 27001:2022‑certified security and role‑based access controls to protect sensitive pricing and sales data