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Tango News


May 20, 2019


Next Gen AI and Machine Learning Capabilities Empower Users to Make More Intelligent Real Estate Location and Development Decisions to Lower Costs, Drive Growth

Texas, May 20, 2019 – Tango, a leader in Store Lifecycle Management (SLM) and Integrated Workplace Management System (IWMS) solutions, today announced its new enhanced TangoAI Platform featuring artificial intelligence (AI) and machine learning for the retail and enterprise markets. TangoAI enables retailers, restaurants and corporate enterprises to make smarter, more informed data-driven decisions around their real estate and facilities strategies that are critical to navigating today’s fast-evolving and disruptive environment, while also keeping capital and operating expenditures low.

“Shifting consumer shopping behaviors and today’s more flexible workplaces are disrupting the retail and corporate real estate industries as we know them,” said Pranav Tyagi, founder, President and CEO of Tango. “Both retail brands and enterprises need to nimbly and strategically respond to these changes to survive and thrive. Tango’s advanced AI-driven approach arms customers with the intelligent insights they need, which were not previously available, to solve longstanding industry challenges and gain a competitive edge.”

Tango is the only solution that brings together strategy, development and management in a single end-to-end solution. The company’s next gen Tango AI platform combines years of traditional modeling and big data experience with leading-edge AI and machine learning to uncover new insights and deliver a higher level of value to real estate strategy and execution.

Tango for Retail

Brick-and-mortar stores have been hurt both by overexpansion and the continued growth of online consumer spending, forcing retailers to think of ways to either downsize their footprints or repurpose their stores. Getting this right has a huge impact on their business viability.

Tango leverages the power of AI to analyze millions of data inputs around market dynamics, operations and performance to provide retailers with the real-time information they need to make proactive, intelligent decisions. Through Tango’s multidimensional AI lens, retailers can ask and answer strategic questions beyond traditional modeling to extract valuable data previously untapped and test out new hypotheses around future store distribution models.

TangoAI Products:

  • Market Optimization – Determine the right number of stores and their locations to maximize market-level revenue and profitability.
  • Sales Forecasting – Elevate traditional modeling techniques with stacked AI and machine learning models that discover new drivers of performance and improve model accuracy.
  • Lease Renewals – Drive lease decisions including renewal, renegotiation or exit based on store performance, sales potential, landlord analytics, trade area quality and market rents.

Tango for Corporate Enterprises

As technological and cultural disruption change the way people work (e.g., flex time, shared working spaces), Tango’s platform helps enterprises better align their physical footprint with both company strategy and employee needs, all while driving down costs. Tango’s next-generation platform employs AI and machine learning to fulfill the often-elusive promise made by mainstream IWMS or point solution providers.

Through evolutionary modeling based on numerous and varied data inputs, Tango helps businesses determine department needs and accessibility for efficient planning. Using pattern recognition algorithms and computational geometry at a CAD and pixel level, Tango recognizes spaces, creates draft polylines and optimizes space utilization.

TangoAI Products:

  • Space Optimization – Generate optimal space layout options that maximize utilization while accounting for departmental affinity, needs, preferences and constraints.
  • Auto-polyline – Dramatically reduce the time required to create polylines, including each with their own quality score.
  • Spatial Recognition – Analyze CAD drawings to identify and classify space, determine usage and enrich data sets.