Don't search for needles.
Get rid of the hayTM.

What is Indāgō?

Indāgō is a content analytics platform that finds, sorts, extracts and classifies unstructured content.

    Indāgō uses state-of-the-art machine learning to:

  • Solve missing or inaccurate data problems,
  • Enable greater business efficiency,
  • Deliver relevant and actionnable insight.

What makes Indāgō different and better?

Agile, Comprehensive, Scalable 

Indāgō searches, crawls, profiles, analyzes, and classifies unstructured data of more than 600 file types from virtually any unstructured data repository.

Visual Classification

 Indāgō uniquely addresses the analytics and classification challenges of scanned, native pdf or Tiff content to deliver greater accuracy than OCR-based approaches.


Intelligent Profiling of Data

 Indāgō provides the ability to quickly profile content through virtually any repository to give Subject Matter Experts, via the interactive dashboard and portal, deep analytical insights into the content.

In-place integration with ECMs

Indāgō is intended to function as a decision-support system to automatically create and enhance content metadata in place and integrate with various ECM systems, SharePoint, G-Suite and other repositories .

Information Security

 Reduces information security, regulatory and corporate compliance vulnerabilities.  Automatically and accurately detects and tags sensitive content (PII, PCI, PHI, restricted or classified content).


Graphical visualization of machine-generated information make it easy for subject-matter experts to quickly review various document concepts, themes or extracted data points.

Indāgō Cross-Industry Use Cases

■ Information security and data loss prevention

■ Information governance

■ Regulatory compliance

■ E-discovery acceleration

■ Business analytics and intelligence

■ Data clean-up, profiling and migration

■ Intelligent capture and process automation

Energy and Utilities

  • PHMSA / EHS audits, compliance
  • Well / land content optimization
  • Asset consolidation
  • Lease / royalty agreements analytics

Finance and Insurance

  • SEC / OCC / CFPB / Dodd-Frank audits and compliance
  • Commercial / retail loan origination
  • Claims analytics
  • Information forensics

Other Industry Examples

  • Intellectual property categorization
  • Business process outsourcing
  • AP Automation
  • Engineering / operational assets consolidation

Indāgō : Agile, Comprehensive, Scalable

According to Gartner's 2016 File Analytics Vendor Landscape report, organizations are struggling with uncontrolled data growth. Risk-aware and cost-conscious organizations are realizing they need a better understanding of their data in order to:

■ Effectively reduce the risk and inefficiencies buried in unstructured data

■ Better manage data in line with governance and policies

■ Optimize data management and storage infrastructure

■ Provide better access to unstructured data

■ Facilitate business use of data that has previously been deemed "dark"

According to a Gartner June 2015 report, for many organizations, 30% to 70% of data is redundant, outdated or trivial (ROT).
Assuming a midsize environment, with between 1PB and 4PB of raw capacity, and a storage total cost of ownership (TCO) of $2,325 per TB raw or $3,092 per TB usable (assuming 75% of raw capacity being usable), this equates to $1,546,000 to $6,184,000 in wasted spending on ROT.
Keeping everything also presents a larger-than-necessary target for hackers. In the December 2014 Sony hack, for example, hackers accessed thousands of emails, including deleted items that never actually "went away."

Haystac Delivers Results

We are Haystac
Launched in 2014, Haystac is the creator and developer of Indāgō, one of the most agile, comprehensive, and scalable content analytics software that is used by customers in financial services and insurance, energy and utilities as well as other regulated and non-regulated industries.
Haystac’s history with solutions for unstructured data begins with the founding by Haystac's co-founders Mr. Barak Tsivkin and Mr. Eli Zukovsky, of an entity called Solaris Development Inc.’s in Boston in 2003. To this day, Solaris’ strategy continues to focus primarily on the development of custom applications leveraging proprietary applications of machine learning technologies for healthcare, with customers such as Massachusetts General Hospital, Partners Healthcare, Boston Children's Hospital and other similar healthcare providers in the Boston area.

Since its launch in 2014, Haystac continues to focus its own developmental resources towards furthering and differentiating its content analytics offering in areas such as advanced machine learning algorithms, scalability, visual classification, as well as integration with leading ECMs and other unstructured content repositories.

In addition to a focused direct sales strategy, Haystac invests significant resources in aggressively seeking out and promoting synergistic relationships with leading system integrators and technology vendors.

Examples of these include strategic relationships established in 2016 with Capgemini (one of the world's foremost providers of consulting, technology and outsourcing services), Access Sciences (a leader in information management and governance, technology, change management, and managed services) and HCL (a global services company that covers the entire gamut of technology solutions and services including infrastructure management, application development, BPO and engineering and R&D services).

Haystac also continues to seek out alliances with complementary technology providers. Successful examples include Google, Oracle, Aodocs, ABBY, BCS Systems and AI Foundry.