Hexanika wins the TiE50 Top Start-up Award at TiEcon 2016 event in Silicon Valley
Hexanika nominated for “2015 TiE50 TOP START-UP”
Hexanika nominated for “Top 100 Promising Big Data Companies” by CIO journal
Hexanika nominated in “500I500 Upcoming Start Ups” by Inc magazine
Hexanika nominated for “Top 100 Promising Big Data Companies” by CIO journal
Hexanika nominated in “500I500 Upcoming Start Ups” by Inc magazine

Products: Ready To Go!

  • Ready to Go – Zero Capex and Low Opex model
  • End-to-end product Solutions that uses scalable computing, distributed computing and parallel processing (Big Data)
  • Adaptable products which complement existing solutions

Solutions: Results Delivered!

  • Industry Focus: Solutions focused for banking industry
  • Unique business model that utilizes cost effective technology and human resources to deliver results
  • Fees based on results delivery
Big Data Governance

Converging & Unifying Data from Multiple Sources

Unique solution based on Hadoop framework for integrating, consolidating, aggregating and managing structured or unstructured data from disparate sources.

Regulatory Solutions

Revolutionary tool for Regulatory Reporting

Innovative solution for the unprecedented challenges faced by US banks in today’s ever-changing banking industry & regulatory environment.


  • Data Governance Solution
  • End to end ‘data readiness service’
  • Use of advanced algorithms & machine learning
  • End-to-End regulatory reporting solution
  • Customizable  and configurable reports
  • Auto updates as per compliance requirements

Use Cases






Evolving bank

  • Data profiling
  • XBRL reporting
  • Data normalization
  • Data consolidation

Anti Money

Automate processes
and utilize Big Data to
comply with AML

  • Real-time screening
  • Client on boarding
  • Reduce false positives


Segmentation and
Customer Relationship

  • K-Clustering
  • Single view of customer
  • Behavior Drivers Analytics


Fines and

  • Real-time Deduplication
  • Internal Audit

Product Specific
(mortgage, credit etc)

Sanitize data to get
one view of customer
across multichannel

  • Data Quality
  • Data Integration
  • Data Profiling
  • Data Mining

NAME: Global Banking & Financial Services Company
SIZE: 100,000 employees in 70 countries
INDUSTRY: Financial Services


  • Problems in reconciliation of same transaction being passed over and presented in multiple data streams
  • Analysts were manually identifying duplicate and inconsistent entries in excel spreadsheets of security sales data.
  • Data lacked standard naming conventions and other attributes like client names, status, unique ID

Help client reconcile data from various different data streams and identify outliers which cannot be identified. Two data streams with similar transaction information but data is presented differently and there is no unique identifier.

Multilevel semantic join based on Hadoop i.e. two hoops of jump and then get joins from there. The schema is for ‘MultiJoin’. Configurable rules engine for validation of incoming and outgoing data and create rules for project

Approximately 25% resource savings identified as currently 75+ people are doing this exercise manually

VC FinTech Demo Day - HEXANIKA

On Aug 3, HEXANIKA’s CEO Yogesh Pandit & CMO Huma Usmani pitched at the Global Investor Demo day to conclude the 12 week VC FinTech Accelerator program powered by FIS Global in William J. Clinton Presidential Center in downtown Little Rock, Arkansas.




Scope of Data Integration

Data[1] integration involves combining data residing in different sources and providing users with a unified view of data. This process becomes significant in a variety of situations, which include both commercial (when two similar companies need to merge their databases) and scientific (combining research results from different bioinformatics repositories) domains. Data integration has increased  as the volume and the need to…


Big Data Adoption Process

Big Data, the current buzz word in the IT and financial space has caught the imagination of a lot of organizations. Studies released in the past year or so have clearly shown that Big Data investments are rising across industries and around the globe[1]. It represents a business adoption paradox: it promises speed, but successful…