Torch.AI - Trust at Scale

TRUST AT SCALE.

Torch.AI solves the hardest parts of making data work for the world's most important organizations.

Torch.AI’s Nexus™ Enhanced Data Orchestration (EDO) transforms entire data ecosystems into trusted, auditable, intelligent assets.

COMMUNICATION SYSTEM

Commercial grade integration functionality which fully implements Enterprise Integration Patterns and packages hundreds of OOTB connectors to the most popular systems, clouds services, and databases.

DATA ENGINEERING

Automated functionality for contextually understanding all facets of a data ecosystem so that data can be made actionable, even if incomplete, flawed, unstructured.

ORCHESTRATION AI

Advanced technology embedded into Nexus, typically powered by ML, for solving notoriously difficult data management issues within enterprise ecosystems.

ANALYTIC AI

Nexus is packaged with domain-specific pretained models that quickly and cheaply enrich existing data. Furthermore, Nexus enables a “bring your own model” strategy to register the client’s own trained models (in virtually any modern ML Framework).

SECURITY

Nexus contains a suite of functionality for maintaining a hardened cyber security posture and tools that make the implementation of common compliance regulations much more straightforward.

"Torch.AI demonstrated a solution in 2 weeks for a mission critical problem we’d been working on, without success, for more than 6 years."

"Today, we lead the market in fraud prevention, detection and customer experience. Without Torch we wouldn’t have been able to fix some real challenges with our approach."

"I see Torch.AI as a kind of trend-setter in this space. They’re looking at entity trust very differently, and they are beginning to disrupt – in a positive way."

“In our first meeting with Torch.AI, they didn’t bring slideware briefings. They sat down and asked, ‘what would you like to know more of?' Then they showed us our world. It was compelling because we saw, in real time, how it works.”

"The results were extraordinary. Lead identification and qualification were up 300% in the first week alone."

"In less than 72 hours, our solution identified and supported remediation of a supplier threat for a critical weapon system."

"Once you get a system put in like this, end to end, you can see things you couldn't see before –where data is slowing, where you're missing, and where change needs to happen."

AN ELEGANT PLATFORM WITH FEATURES THAT WILL REVOLUTIONIZE YOUR TEAM'S APPROACH TO SOLVING TOUGH PROBLEMS.

A Better Infrastructure

Torch.AI’s Nexus EDO platform functions as a “smart” enterprise communication system that provides machine learning enhanced data transformations, ingesting data of any type from any source. Our solution was architected with foundational goals of scalability, modularity and auditability.

Automate the grunt work

Our framework enables comprehensive extract-transform-load (ETL) capabilities as well as sophisticated tagging on ingest to rapidly organize and correlate critical information for improved utilization, performance capacity to support “big data”, and better downstream analysis.

Intelligent tagging

Torch.AI pioneered a patent-pending method of enhancing data in real-time through an extensive library of machine learning algorithms. ML-enabled workflows range from OCR and other unstructured data identification, NLP, and sentiment analysis.

Empower analysts

Nexus not only automates daily processes but also extracts more meaning from each process. Workflows range from notifying an analyst of an anomaly and its potential impact, to recalculating risk or complexity scores.

Seamless integration

The Nexus platform will seamlessly integrate into, not disrupt, your existing data infrastructure. We provide the capability to communicate through virtually any protocol, including REST, SOAP, File IQ, EDO, and SQL, and can retrieve content from any source, including relational warehouse, graph, lake or noSQL database.

Secure every step

Torch.AI takes security seriously, from architectural design to code security and data protection, both at rest and in-motion.  Our experience reinforces the value we place on quality assurance, both in penetration testing and mitigating critical vulnerabilities.

NEXUS™ FOR REAL TIME TRANSACTION INTELLIGENCE

Enhanced data object tagging and machine learning for transaction transformations

Quickly adapting to changes in user behavior in high volume transaction applications is notoriously difficult. Each adverse transaction can create significant financial loss and expose companies to potentially serious compliance risk. Torch has been successfully deployed to address complex data orchestration challenges in harsh IT environments at both commercial and federal clients with large-scale requirements.

The primary reason for this lack of capability resides at the data management layer. For one such financial services firm, one of the most important in the U.S., Torch solved this gap in a matter of days by deploying Torch’s Nexus™ EDO platform to transform the way the company ingested and prepared data for real time analysis.

Prior to the Nexus deployment, operations relied on accessing data at rest within multiple secure, disparate, and voluminous database architectures—complex clusters for business, personal, and user activity—with no way to normalize or correlate the data among them. Workflows were largely analog: team members gathered and parsed data, analyzed reports, and conducted investigations.

No longer relegated to applying models and rules to discrete fields due to database and compute limitations, the company reduced false positives boosting customer satisfaction, and reduced fraudulent transactions to a new industry benchmark. All while reducing more than 320 hours of data retrieval, preparation, and analysis work. Nexus also provided additional security enhancements as well to better manage and protect highly sensitive personal information at enterprise scale.

NEXUS™ FOR FRAUD PROPENSITY MODELING

Preventing improper payments on fraudulent claims with OSINT

The US Department of Agriculture's (USDA) Supplemental Nutrition Assistance Program (SNAP) sought to reduce fraud, waste, and abuse within its Food Security programs. Food security means access by all people at all times to have enough food for an active, healthy life.

Utilizing the Nexus™ EDO platform, existing redemption retailer data could now be correlated with open source intelligence (OSINT), primarily from social networks and the Dark Web. USDA’s solution is able to identify and track illegal SNAP transactions initiated or transacted across the internet and alert appropriate parties for remediation. Within just one target geography, more than one hundred at risk retailers were identified using only publicly available data.

Typically, a “pay and chase” approach is used to identify and recoup an improper payment after processing. This practice is labor intensive and results in a low recovery rate. The Torch solution can identify fraud before payment by deploying machine learning to screening for the most common themes, geo-rectifying users to stores, and augmenting decision rubrics with OSINT. By continuously surfacing data and detecting linkage within the network, government agencies can rapidly and cost effectively monitor for risks and vulnerabilities, and most importantly, solve them.

NEXUS™ FOR GLOBAL MARKETING

Linking deeply mined, loosely coupled data objects for improved relevance and timing.

In the highly competitive software and database marketplace, deeper understanding of customers, buying intent, and correlation become weapons. Indeed the Cloud market has grown to more than $266 billion. Driven to gain market share in this complex environment, Microsoft leveraged the Torch platform to ingest, tag, and transform data to enable a holistic understanding of various but interconnected entities: software developers, marketing campaigns, competitors, companies, media, and influencers. Not only did Torch provide a deeper understanding of key entities but went one step further to illuminate complex relationships among the players, creating a battle map for market penetration, talent acquisition and the purchase decision-maker network.

The Torch platform produced data scientist friendly payloads to rapidly visualize findings obtained from correlating multiple data sources in a comprehensive multidimension output, with drill-down to event-specific transactions. This helped employees better communicate opportunities to various constituencies across the company.

A view on the Microsoft market ecosystem was created, identifying high-level influencers for future marketing strategy development .The platform leveraged tagging data in flight to generate more responsive, relevant, and responsible tactics for engaging Microsoft’s customer base.

NEXUS™ FOR SUPPLY CHAIN SECURITY

Tagging of atomic data objects to describe and score relationships

The global economy presents unique and complex challenges when applying risk methodologies with the goal of safeguarding government and large commercial supply chains from emerging threats and vulnerabilities.

Torch pioneered an evolved approach to identifying, assessing, and neutralizing risks associated with the global and distributed nature of product and service supply chains. Nexus™ EDO provides a unique capability due to the platform’s ability to collect vast data, unpack and tag each data object at the atomic level, and utilize machine learning to determine and predict relationships across loosely coupled networks.

The presence and influence of adversarial foreign government influence, poor manufacturing and development practices, counterfeit products, tampering, theft, and malicious software are examples of supply chain risks that must be mitigated. Federal agencies, government contractors, suppliers, and integrators use varied and non-standardized practices, making it difficult to consistently evaluate, measure, and neutralize threats to a supply chain.

Torch has developed several specialized software solutions that autonomously interrogate complex networks that can be concurrently persistent and ad-hoc, solving several challenges in the Supply Chain Risk Management sector.