The second part of the post on 'AI for Enterprises' titled ‘AI for Enterprises. Part-2: Metrics for Matriculates?’ has been released on October 25, 2022 at the MassTLC website and the corresponding extended version titled ‘AI for Enterprises. Part-2: Metrics for Matriculates? [Extended version]’ at ReSurfX (this) website. The approach taken in this post was similar to the previous post in the context of data quality and data utilization in the previous post ‘AI for enterprises. Part-1: Where are we in tackling the popular adage GIGO?’. With focus on data quality (garbage-in-garbage-out) as the central theme – that previous post also had a companion version ‘AI for enterprises. Part-1: Where are we in tackling the popular adage GIGO? [Extended Version]’ in this website that included more details on ReSurfX solutions. In both cases the extended version had lot more information on ability of ReSurfX solutions to deliver superior outcomes in part by tackling problems and pitfalls outlined in the posts and approaches outlined to overcome them. The second part of the post focused on proper use of metrics in establishing and expansion of (deriving value from) digital transformation and artificial intelligence (AI) in enterprises much more than technical aspects, including aspects such as enterprise architecture and roll out problems. The point was more about use of classical metrics when they are inadequate or when their use are is inappropriate – hence need to design new ones, the capability to do that and knowing these is are important for enterprises which also allow them to be open to adopt them. The post also covered many bite sized concepts of guiding principles used across all initiatives at ReSurfX when designing product functionalities or in discussing relevance of new findings in the context of value to customers. Together these two posts covered lot of grounds in effective data utilization both as improvement in efficiency and innovation (as prediction of insights – reliably detecting known insights that typically are difficult to predict even with lot of data and resources as well novel insights to guide decisions) for better outcomes vertically across enterprise operations.

The two posts tied together the problems, pitfalls and solutions and moved on to discuss how ReSurfX handles these in addition to leveraging the novel data-source agnostic (hence sector agnostic) machine learning approach “Adaptive Hypersurface Technology (AHT)” which lead to development of incredibly powerful functionalities and product yielding valuable results improving outcomes, innovation and return on investment (ROI) of enterprises. Lot more details of the enterprise SaaS product of ReSurfX, ReSurfX::vysen, and results derived from them were covered in the extended versions of the posts in ReSurfX website. The extended versions also covered the immense depth in motivating factors behind the choice of the beachhead data/technology of ReSurfX::vysen from multiple key perspectives including data, machine learning (ML) to prove their value as well as the incredible increase in information content.

When asked if he would like to add anything besides what he covered in this article, our CEO and Cofounder Suresh Gopalan said:

1. The results we added there speak for themselves. When thinking of the power and reliability they convey even from the small fraction we have shared publicly I am reminded of a statement by a research based customer from a healthcare system who when talking to us about value remarked: “when it comes to insights or aiding improvement for that, it is difficult to put a value on it, as the right one is priceless”. That statement is understandable as many advances in life sciences and healthcare (including patient care solutions and decision support) are result of novel insights that are few and far between and result of a long and protracted effort. I am very pleased that our culture at ReSurfX also places high value on customer feedback.
2. Suresh also added when putting together the simplistic pictorial depiction of SyRTOP configuration used in extended version in second part of the posts he was reminded of the first question our tech lead asked about the picture (which he did not get to see before release) in our post ReSurfX in 2021 – Best-in-class Outcome Predictors, Innovation Catalysts and ROI Multipliers. He said the question was “why the pictorial in that post did not include a data lake which is of incredible value to customers – as data ingestion layer remains a big pain point for most enterprises, and the variation of data lake concept that we use at ReSurfX is so much ahead of most solutions in the market”.
3. How our product and functionalities are built and their power are reflected in results shared some of which are articulated in these posts – but what could not be expressed adequately in the posts is the pleasure in working with incredibly talented team where each member is focused on the same set of values.

Consistent with comments mentioned earlier, our CEO expressed that sentiment by sharing the post on in LinkedIn® as: “AI for Enterprises. Part-2: Metrics for Matriculates? [Extended]’ covers technical through enterprise architecture aspects in adopting the AI wave. I highlight seemingly simple guiding themes we use at ReSurfX that help our awesome team develop immensely creative, powerful and robust solutions for complex problems of great value to customers.”.

We are pleased to share that the first part of a two-part post on AI for Enterprises in their website. Part 1 focused on data quality effects titled - "AI for Enterprises. Part 1: Where Are We in Tackling the Popular Adage GIGO?" is published by the Massachusetts Technology Leadership Council (MassTLC). The post by our CEO, Suresh Gopalan, centered on the current status in tackling data quality, effects on outcomes and consequently on designing robust and effective digital and AI transformation strategies. The post outlined ReSurfX solutions where we leverage our novel machine learning approach 'Adaptive Hypersurface Technology' (AHT) in our emerging solutions as well as the ones already in the enterprise SaaS product ReSurfX::vysen. The post highlighted causes for current problems, implications, current efforts and ReSurfX solution based on the premise that our CEO Suresh Gopalan had highlighted in the showcase interview published CIO Review in 2017 together with ReSurfX being recognized as 20 Most Promising Data Analytics Solution Providers in 2017. The premise we posited while building AHT and solutions for our customers currently though the SaaS product ReSurfX::vysen is that: “dramatic improvements in accuracy and novel insights can only happen through innovation outside the mainstream framework – given that error properties are often non-uniform in big data, and most analytic shortcomings result from model assumptions not robust enough to handle that”. That approach has proven very effective in every solution we develop and tested in scale have proven to be the "best-in-class". Suresh Gopalan expressed not only expressed his thanks to our team who continue to explore, innovate, build and execute these powerful solutions, as well as our MassTLC and their team for spotlighting that post in their newsletter of June 22, 2022. A section with the copy from that spotlight in MassTLC newsletter is here.

A longer version of above-mentioned post with same title, but with more details is posted on our website which covers the solutions in ReSurfX::vysen product, unprecedented outcomes and proof of every value proposition of ReSurfX from the beachhead applications using gene expression, broader applicability based on the data properties, and additional rationale for that choice.

We had published our prediction solution termed System Response based Triggers and Outcomes Prediction (SyRTOP) earlier in January 2020 titled ReSurfX::vysen Yields Remarkably Accurate and Actionable Insights Using System Response to Triggers – A Drug Response Study. Recently we published more results based on validation of both the solution and productized functionality at scale together with broader implications and outlook of our functionalities roll-out for enterprise scale and vertical as well as horizontal applications in business chain in the healthcare sector titled ReSurfX in 2021 - Best-in-class Outcome Predictors, Innovation Catalysts and ROI Multipliers.

We took the opportunity to also clarify that the set of functionalities including the analytics modules, total system response based prediction modules used here forms an application configuration that is SyRTOP, as we found that the phrasing in the previous post on SyRTOP gave the opportunity for just the predictor module to be misconstrued as SyRTOP.

The at-scale validation of predictions from these functional modules leveraging AHT provided proof of immense value added by each functional module as well as the ability to predict far downstream events from even a single system status reporter. For example, SyRTOP predicted multiple instances of drug combination effects that had been recognized by the US Food and Drug Administration (FDA) as well as the American Heart Association (AHA) based on post-market surveillance (PMS). Those results also demonstrated the presence of over 30% errors in processed and compiled information used for making decisions by ML/AI solutions (naturally, by humans as well). Over the large scale of validation we also found that these characteristics of ReSurfX solutions leveraging AHT are the norm rather than exception. Given the multiple use configurations and deliverables from the product we  accomplished these in approaches that are data-source, data-formats and data-storage infrastructure agnostic - simplistically relatable to the data-lake approach that is getting commoditized. As to development of functional modules AHT is data-source agnostic.

On commenting about those results our CEO, Suresh Gopalan, summarized the impact as follows.

• These results even from the small portion of results we have released through this use case proves every value proposition of ReSurfX to significantly improve outcomes, innovation and ROI of enterprises. The results address accuracy, novelty and robustness of both the analytics components and the prediction components, as well as advance prediction of outcome directions.
• In addition to creatively leveraging the powerful mothership technology, these results (i) indicate that our powerful data designs for validation is also major factor in success of using AI (data-based decisions in general and through ML); (ii) highlight the incredible value that can be realized from the new insights ReSurfX solutions can generate by way of elucidating outcomes considered 'Real World Evidence' (RWE) from what is termed 'Real World Data'. Such RWE are usually difficult to achieve even through targeted validation, whereas ReSurfX solutions obtained them using much simpler data.
• We further made customer-centric decision to make offshoot deliverables to provide accurate Knowledge Repositories (KRs)  to enable our customers to build custom (and proprietary) repositories to  improve their workflows that use other solutions, in formats that confer cost-effectiveness in reducing some repeat steps involved in generating predictions from AI solutions. These are incredibly valuable to enterprises not only in using our powerful and generalized adapt-for-need-modules made leveraging AHT, but also all other part of their workflows in an integrative manner.

We continue to add newer functionalities with capabilities to glean value metrics evident to our customers at all stages.

Introducing a powerful functional module SyRTOP to predict triggers and outcomes from the response of a system ('systems response') to our outcomes intelligence SaaS  product ReSurfX::vysen. These solutions are both artificial intelligence and expert enablers (where human intelligence is paramount). We have released information on how our powerful and novel 'data-source agnostic' machine learning approach 'Adaptive Hypersurface Technology' (AHT) is one of the most powerful solution when many combinations of inputs can lead to the same outcome. Variety of data sources are becoming available as is the ease to incorporate these into cause and outcomes determination workflows including in our target sectors Pharma, biotech and healthcare. We have now introduced a powerful new solution (SyRTOP) as a functional module to ReSurfX::vysen to gain insights on the causes and effects (and side-effects) of actions/treatments to alter them effectively (e.g., in patient outcomes, clinical trials, high cost treatments). Learn more about this solution here using a drug response case study - ReSurfX::vysen Yields Remarkably Accurate and Actionable Insights Using System Response to Triggers – A Drug Response Study. We also demonstrate that the solution we offer is far more accurate than widely used public domain and and commercial product solutions (that were among the best of available solutions). During our efforts found that 'current Knowledge Repositories (backend databases) have more than 30% errors', indicating a cause why even the most powerful infrastructure and solutions often don't live up to their hype.

Together with this module we also incorporated a continually increasing Knowledge Repository into ReSurfX::vysen, and Big Data solutions to help our customers make accurate knowledge sources even from their proprietary data.

While drug response is used as an example here, the value of SyRTOP solves various needs says Suresh Gopalan, our CEO and Founder - just in our initial target sectors applications include predicting patient outcomes, knowing unexpected outcomes, monitoring deviations from predicted behavior in clinical trials. He goes on to add that we are proud of our awesome team to innovate and incorporate another 'best in class' solution into ReSurfX::vysen enterprise SaaS product.

Releasing powerful and secure REST APIs and SDKs to our outcomes intelligence product enterprise SaaS product ReSurfX::vysen. A popular request from our customers to whom we are building end-to-end enterprise solutions for vertical integration and use, is ease of integration. We are proud of our leadership and technical teams for thoughtful and clean development of these additional functionalities says our Founder and CEO - Suresh Gopalan. This addition with our focus on end-to-end and 'best in class' applications that are continually added to our offerings help many classes of ongoing and upcoming data-intensive initiatives for and with our customers have significant impact on their ROI as captured in the simple pictorial below.

Key considerations in our product design strategy, besides smooth user interactions including in these APIs with well defined end-points and SDK wrappers that combine them as functional modules in addition through our interfaces (UI) in the web application. An example is the remark from a customer that "this is a remarkably smooth UI for a heavy grade application product of this nature".

We release a blog by Suresh Gopalan (our CEO and Founder) highlighting how we use 'combinatorics' and 'dimensionality' in solutions ReSurfX offer leveraging our novel machine learning solution 'Adaptive Hypersurface Technology' AHT. Typically both these aspects are considered problems including through the terms 'Curse of Dimensionality' and 'Combinatorial Explosion' in the use of Big Data. Some of our customers who personally have attempted to solve these problems or have tried other solutions share that they were stumped by these problems. Read more in our vysdom blog series 'Overcoming the Curse of Dimensionality with Combinatorics'.

ReSurfX, recently recognized as '20 Most Promising Data Analytics Vendors' by CIOReview is happy to announce accessibility of our SaaS product vysen (THE MOST ACCURATE IN THE MARKET) to more class of customers by pricing based on volume usage. Now we have expanded the access beyond the previous target of enterprise customers alone. Our value add is in line with many other accolades based on what we bring to the market and customers - including as an 'emerging company defining the next generation of personalized medicine platforms and technologies'.

ReSurfX has been recognized the "20 Most Promising Data Analytics Solutions Providers - 2017" by CIOReview magazine. We consider this a great honor that our creativity, value to market and customer centricity is recognized yet another time.

The list of 20 Companies can be seen here: //data-analytics.cioreview.com/vendors/2017/

The profile of our company has been published in online format online format and magazine format .

Click to view a local copy of the article here.

Another patent issued to ReSurfX in Israel. This is the 10th issued patent of ReSurfX, and expands the geographical scope of already very strong IP and patent portfolio of ReSurfX. The patent relates to parts of core technology invented by Suresh Gopalan, our CEO and Founder.

ReSurfX is proud to release our new version of our SaaS product ReSurfX::vysen 2.0 & a 30-day free trial version.

This version features an awesome UI/UX tailored with modern features characteristic of smartphone generation not typically found in heavy duty analytics products. vysen 2.0 features great infrastructure built by experts with extreme security, scalability and customer enterprise integration perspective. The product is capable of repository scale processing and packs in the signature accuracy and innovation power, leveraging our novel 'Adaptive Hypersurface Technology' (AHT).