RPA Solutions

AiSensum offers RPA (Robotic Process Automation) modules
to help clients realise the full value of their data.

These AI modules are designed to sit within legacy systems and help improve system performance over time. They are low cost bets for companies who are unwilling or unable to invest in fully automated AI platforms.

AiSensum have experience in all sectors and verticals and in all sizes of business.

Here are some of our RPA Ai Software!

  • Marketing Mix Optimization helps marketers allocate approximately across BTL and ATL promotional methods.


  • Entry Price Points (EPP) and optimal price ranges for each brand and category based on price elasticity.

  • Promo Planning Software to decrease marketing costs on low sales margins and boost impactful promotions.


  • AI Based Customer Profiling provides you with a micro-cluster level view of your CRM. Prioritizing marketing & customer service efforts.

  • Customer Portfolio Expansion modelling and personalized CRM activities to increase customer base.

  • Proactive customer retention by predicting lapsing probability, up to eight weeks in advance.
  • E-Commerce path to purchases using clickstream data from leading E-Commerce websites.

  • Search Optimization for favourable e-search results for your product.

  • E-Assortment recommendations, outlining most preferred path to purchase your products.


  • Webscrapping and Webcrawling software to understand key activities on your Brand areas.

    Providing real time information on key trends to help draw action plan to maximize it.

    Assortment recommendationsoutlining most likely New Product Combinations for success.

  • Brand Line Extension opportunities by identifying emerging customer needs and trends.

  • Optimal range recommendations by Brand for modern trade retailers.

  • New product launch recommendations and performance tracking.
  • AI Based Demand Forecasting which will accurately predict demand for your brands.

  • Forecast Segmented into region, channels and variants accommodating business constrains, season and external factors.

  • Adjustments for product lifecycle and emerging channels such as E-Commerce.
    • Distribution alerts segmented by product, area and delivery window to improve product availability.

    • Ability to integrate with the present stock ordering system, to decrease system replacement costs.

    • Out of stock alerts per poste code area.


  • Sales demand allocation by each sales territory to balance workload optimization across sales force.

  • Sales force field plan recommendations – to better align organizational goals with field activities.

  • Sales force incentive compensation planning and reporting.
  • Creating structured data lake of IoT inputs for business reporting and decision making.

    Analyzing IoT devices signals using AI to accurately forecast probability of defects.

    Increasing preventive maintenance window to improve overall production throughput.